Merge branch 'next' of https://github.com/eyaltoledano/claude-task-master into joedanz/flexible-brand-rules

# Conflicts:
#	scripts/modules/commands.js
#	scripts/modules/ui.js
This commit is contained in:
Joe Danziger
2025-05-19 11:16:29 -04:00
123 changed files with 7224 additions and 1761 deletions

View File

@@ -32,7 +32,7 @@ The script can be configured through environment variables in a `.env` file at t
- `PERPLEXITY_API_KEY`: Your Perplexity API key for research-backed subtask generation
- `PERPLEXITY_MODEL`: Specify which Perplexity model to use (default: "sonar-medium-online")
- `DEBUG`: Enable debug logging (default: false)
- `LOG_LEVEL`: Log level - debug, info, warn, error (default: info)
- `TASKMASTER_LOG_LEVEL`: Log level - debug, info, warn, error (default: info)
- `DEFAULT_SUBTASKS`: Default number of subtasks when expanding (default: 3)
- `DEFAULT_PRIORITY`: Default priority for generated tasks (default: medium)
- `PROJECT_NAME`: Override default project name in tasks.json
@@ -47,7 +47,7 @@ The script can be configured through environment variables in a `.env` file at t
- Tasks can have `subtasks` for more detailed implementation steps.
- Dependencies are displayed with status indicators (✅ for completed, ⏱️ for pending) to easily track progress.
2. **Script Commands**
2. **Script Commands**
You can run the script via:
```bash
@@ -225,7 +225,7 @@ To use the Perplexity integration:
## Logging
The script supports different logging levels controlled by the `LOG_LEVEL` environment variable:
The script supports different logging levels controlled by the `TASKMASTER_LOG_LEVEL` environment variable:
- `debug`: Detailed information, typically useful for troubleshooting
- `info`: Confirmation that things are working as expected (default)

View File

@@ -40,10 +40,10 @@ const LOG_LEVELS = {
success: 4
};
// Get log level from environment or default to info
const LOG_LEVEL = process.env.LOG_LEVEL
? LOG_LEVELS[process.env.LOG_LEVEL.toLowerCase()]
: LOG_LEVELS.info;
// Determine log level from environment variable or default to 'info'
const LOG_LEVEL = process.env.TASKMASTER_LOG_LEVEL
? LOG_LEVELS[process.env.TASKMASTER_LOG_LEVEL.toLowerCase()]
: LOG_LEVELS.info; // Default to info
// Create a color gradient for the banner
const coolGradient = gradient(['#00b4d8', '#0077b6', '#03045e']);

View File

@@ -14,9 +14,13 @@ import {
getResearchModelId,
getFallbackProvider,
getFallbackModelId,
getParametersForRole
getParametersForRole,
getUserId,
MODEL_MAP,
getDebugFlag,
getBaseUrlForRole
} from './config-manager.js';
import { log, resolveEnvVariable, findProjectRoot } from './utils.js';
import { log, resolveEnvVariable, isSilentMode } from './utils.js';
import * as anthropic from '../../src/ai-providers/anthropic.js';
import * as perplexity from '../../src/ai-providers/perplexity.js';
@@ -24,8 +28,39 @@ import * as google from '../../src/ai-providers/google.js';
import * as openai from '../../src/ai-providers/openai.js';
import * as xai from '../../src/ai-providers/xai.js';
import * as openrouter from '../../src/ai-providers/openrouter.js';
import * as ollama from '../../src/ai-providers/ollama.js';
// TODO: Import other provider modules when implemented (ollama, etc.)
// Helper function to get cost for a specific model
function _getCostForModel(providerName, modelId) {
if (!MODEL_MAP || !MODEL_MAP[providerName]) {
log(
'warn',
`Provider "${providerName}" not found in MODEL_MAP. Cannot determine cost for model ${modelId}.`
);
return { inputCost: 0, outputCost: 0, currency: 'USD' }; // Default to zero cost
}
const modelData = MODEL_MAP[providerName].find((m) => m.id === modelId);
if (!modelData || !modelData.cost_per_1m_tokens) {
log(
'debug',
`Cost data not found for model "${modelId}" under provider "${providerName}". Assuming zero cost.`
);
return { inputCost: 0, outputCost: 0, currency: 'USD' }; // Default to zero cost
}
// Ensure currency is part of the returned object, defaulting if not present
const currency = modelData.cost_per_1m_tokens.currency || 'USD';
return {
inputCost: modelData.cost_per_1m_tokens.input || 0,
outputCost: modelData.cost_per_1m_tokens.output || 0,
currency: currency
};
}
// --- Provider Function Map ---
// Maps provider names (lowercase) to their respective service functions
const PROVIDER_FUNCTIONS = {
@@ -62,6 +97,11 @@ const PROVIDER_FUNCTIONS = {
generateText: openrouter.generateOpenRouterText,
streamText: openrouter.streamOpenRouterText,
generateObject: openrouter.generateOpenRouterObject
},
ollama: {
generateText: ollama.generateOllamaText,
streamText: ollama.streamOllamaText,
generateObject: ollama.generateOllamaObject
}
// TODO: Add entries for ollama, etc. when implemented
};
@@ -149,14 +189,10 @@ function _resolveApiKey(providerName, session, projectRoot = null) {
mistral: 'MISTRAL_API_KEY',
azure: 'AZURE_OPENAI_API_KEY',
openrouter: 'OPENROUTER_API_KEY',
xai: 'XAI_API_KEY'
xai: 'XAI_API_KEY',
ollama: 'OLLAMA_API_KEY'
};
// Double check this -- I have had to use an api key for ollama in the past
// if (providerName === 'ollama') {
// return null; // Ollama typically doesn't require an API key for basic setup
// }
const envVarName = keyMap[providerName];
if (!envVarName) {
throw new Error(
@@ -165,6 +201,13 @@ function _resolveApiKey(providerName, session, projectRoot = null) {
}
const apiKey = resolveEnvVariable(envVarName, session, projectRoot);
// Special handling for Ollama - API key is optional
if (providerName === 'ollama') {
return apiKey || null;
}
// For all other providers, API key is required
if (!apiKey) {
throw new Error(
`Required API key ${envVarName} for provider '${providerName}' is not set in environment, session, or .env file.`
@@ -196,18 +239,22 @@ async function _attemptProviderCallWithRetries(
while (retries <= MAX_RETRIES) {
try {
log(
'info',
`Attempt ${retries + 1}/${MAX_RETRIES + 1} calling ${fnName} (Provider: ${providerName}, Model: ${modelId}, Role: ${attemptRole})`
);
if (getDebugFlag()) {
log(
'info',
`Attempt ${retries + 1}/${MAX_RETRIES + 1} calling ${fnName} (Provider: ${providerName}, Model: ${modelId}, Role: ${attemptRole})`
);
}
// Call the specific provider function directly
const result = await providerApiFn(callParams);
log(
'info',
`${fnName} succeeded for role ${attemptRole} (Provider: ${providerName}) on attempt ${retries + 1}`
);
if (getDebugFlag()) {
log(
'info',
`${fnName} succeeded for role ${attemptRole} (Provider: ${providerName}) on attempt ${retries + 1}`
);
}
return result;
} catch (error) {
log(
@@ -220,13 +267,13 @@ async function _attemptProviderCallWithRetries(
const delay = INITIAL_RETRY_DELAY_MS * Math.pow(2, retries - 1);
log(
'info',
`Retryable error detected. Retrying in ${delay / 1000}s...`
`Something went wrong on the provider side. Retrying in ${delay / 1000}s...`
);
await new Promise((resolve) => setTimeout(resolve, delay));
} else {
log(
'error',
`Non-retryable error or max retries reached for role ${attemptRole} (${fnName} / ${providerName}).`
`Something went wrong on the provider side. Max retries reached for role ${attemptRole} (${fnName} / ${providerName}).`
);
throw error;
}
@@ -242,7 +289,15 @@ async function _attemptProviderCallWithRetries(
* Base logic for unified service functions.
* @param {string} serviceType - Type of service ('generateText', 'streamText', 'generateObject').
* @param {object} params - Original parameters passed to the service function.
* @param {string} params.role - The initial client role.
* @param {object} [params.session=null] - Optional MCP session object.
* @param {string} [params.projectRoot] - Optional project root path.
* @param {string} params.commandName - Name of the command invoking the service.
* @param {string} params.outputType - 'cli' or 'mcp'.
* @param {string} [params.systemPrompt] - Optional system prompt.
* @param {string} [params.prompt] - The prompt for the AI.
* @param {string} [params.schema] - The Zod schema for the expected object.
* @param {string} [params.objectName] - Name for object/tool.
* @returns {Promise<any>} Result from the underlying provider call.
*/
async function _unifiedServiceRunner(serviceType, params) {
@@ -254,15 +309,25 @@ async function _unifiedServiceRunner(serviceType, params) {
prompt,
schema,
objectName,
commandName,
outputType,
...restApiParams
} = params;
log('info', `${serviceType}Service called`, {
role: initialRole,
projectRoot
});
if (getDebugFlag()) {
log('info', `${serviceType}Service called`, {
role: initialRole,
commandName,
outputType,
projectRoot
});
}
// Determine the effective project root (passed in or detected)
const effectiveProjectRoot = projectRoot || findProjectRoot();
// Determine the effective project root (passed in or detected if needed by config getters)
const { findProjectRoot: detectProjectRoot } = await import('./utils.js'); // Dynamically import if needed
const effectiveProjectRoot = projectRoot || detectProjectRoot();
// Get userId from config - ensure effectiveProjectRoot is passed
const userId = getUserId(effectiveProjectRoot);
let sequence;
if (initialRole === 'main') {
@@ -284,7 +349,15 @@ async function _unifiedServiceRunner(serviceType, params) {
'AI service call failed for all configured roles.';
for (const currentRole of sequence) {
let providerName, modelId, apiKey, roleParams, providerFnSet, providerApiFn;
let providerName,
modelId,
apiKey,
roleParams,
providerFnSet,
providerApiFn,
baseUrl,
providerResponse,
telemetryData = null;
try {
log('info', `New AI service call with role: ${currentRole}`);
@@ -325,6 +398,7 @@ async function _unifiedServiceRunner(serviceType, params) {
// Pass effectiveProjectRoot to getParametersForRole
roleParams = getParametersForRole(currentRole, effectiveProjectRoot);
baseUrl = getBaseUrlForRole(currentRole, effectiveProjectRoot);
// 2. Get Provider Function Set
providerFnSet = PROVIDER_FUNCTIONS[providerName?.toLowerCase()];
@@ -401,12 +475,13 @@ async function _unifiedServiceRunner(serviceType, params) {
maxTokens: roleParams.maxTokens,
temperature: roleParams.temperature,
messages,
baseUrl,
...(serviceType === 'generateObject' && { schema, objectName }),
...restApiParams
};
// 6. Attempt the call with retries
const result = await _attemptProviderCallWithRetries(
providerResponse = await _attemptProviderCallWithRetries(
providerApiFn,
callParams,
providerName,
@@ -414,9 +489,53 @@ async function _unifiedServiceRunner(serviceType, params) {
currentRole
);
log('info', `${serviceType}Service succeeded using role: ${currentRole}`);
// --- Log Telemetry & Capture Data ---
// Use providerResponse which contains the usage data directly for text/object
if (userId && providerResponse && providerResponse.usage) {
try {
telemetryData = await logAiUsage({
userId,
commandName,
providerName,
modelId,
inputTokens: providerResponse.usage.inputTokens,
outputTokens: providerResponse.usage.outputTokens,
outputType
});
} catch (telemetryError) {
// logAiUsage already logs its own errors and returns null on failure
// No need to log again here, telemetryData will remain null
}
} else if (userId && providerResponse && !providerResponse.usage) {
log(
'warn',
`Cannot log telemetry for ${commandName} (${providerName}/${modelId}): AI result missing 'usage' data. (May be expected for streams)`
);
}
// --- End Log Telemetry ---
return result;
// --- Extract the correct main result based on serviceType ---
let finalMainResult;
if (serviceType === 'generateText') {
finalMainResult = providerResponse.text;
} else if (serviceType === 'generateObject') {
finalMainResult = providerResponse.object;
} else if (serviceType === 'streamText') {
finalMainResult = providerResponse; // Return the whole stream object
} else {
log(
'error',
`Unknown serviceType in _unifiedServiceRunner: ${serviceType}`
);
finalMainResult = providerResponse; // Default to returning the whole object as fallback
}
// --- End Main Result Extraction ---
// Return a composite object including the extracted main result and telemetry data
return {
mainResult: finalMainResult,
telemetryData: telemetryData
};
} catch (error) {
const cleanMessage = _extractErrorMessage(error);
log(
@@ -461,11 +580,16 @@ async function _unifiedServiceRunner(serviceType, params) {
* @param {string} [params.projectRoot=null] - Optional project root path for .env fallback.
* @param {string} params.prompt - The prompt for the AI.
* @param {string} [params.systemPrompt] - Optional system prompt.
* // Other specific generateText params can be included here.
* @returns {Promise<string>} The generated text content.
* @param {string} params.commandName - Name of the command invoking the service.
* @param {string} [params.outputType='cli'] - 'cli' or 'mcp'.
* @returns {Promise<object>} Result object containing generated text and usage data.
*/
async function generateTextService(params) {
return _unifiedServiceRunner('generateText', params);
// Ensure default outputType if not provided
const defaults = { outputType: 'cli' };
const combinedParams = { ...defaults, ...params };
// TODO: Validate commandName exists?
return _unifiedServiceRunner('generateText', combinedParams);
}
/**
@@ -478,11 +602,18 @@ async function generateTextService(params) {
* @param {string} [params.projectRoot=null] - Optional project root path for .env fallback.
* @param {string} params.prompt - The prompt for the AI.
* @param {string} [params.systemPrompt] - Optional system prompt.
* // Other specific streamText params can be included here.
* @returns {Promise<ReadableStream<string>>} A readable stream of text deltas.
* @param {string} params.commandName - Name of the command invoking the service.
* @param {string} [params.outputType='cli'] - 'cli' or 'mcp'.
* @returns {Promise<object>} Result object containing the stream and usage data.
*/
async function streamTextService(params) {
return _unifiedServiceRunner('streamText', params);
const defaults = { outputType: 'cli' };
const combinedParams = { ...defaults, ...params };
// TODO: Validate commandName exists?
// NOTE: Telemetry for streaming might be tricky as usage data often comes at the end.
// The current implementation logs *after* the stream is returned.
// We might need to adjust how usage is captured/logged for streams.
return _unifiedServiceRunner('streamText', combinedParams);
}
/**
@@ -498,15 +629,89 @@ async function streamTextService(params) {
* @param {string} [params.systemPrompt] - Optional system prompt.
* @param {string} [params.objectName='generated_object'] - Name for object/tool.
* @param {number} [params.maxRetries=3] - Max retries for object generation.
* @returns {Promise<object>} The generated object matching the schema.
* @param {string} params.commandName - Name of the command invoking the service.
* @param {string} [params.outputType='cli'] - 'cli' or 'mcp'.
* @returns {Promise<object>} Result object containing the generated object and usage data.
*/
async function generateObjectService(params) {
const defaults = {
objectName: 'generated_object',
maxRetries: 3
maxRetries: 3,
outputType: 'cli'
};
const combinedParams = { ...defaults, ...params };
// TODO: Validate commandName exists?
return _unifiedServiceRunner('generateObject', combinedParams);
}
export { generateTextService, streamTextService, generateObjectService };
// --- Telemetry Function ---
/**
* Logs AI usage telemetry data.
* For now, it just logs to the console. Sending will be implemented later.
* @param {object} params - Telemetry parameters.
* @param {string} params.userId - Unique user identifier.
* @param {string} params.commandName - The command that triggered the AI call.
* @param {string} params.providerName - The AI provider used (e.g., 'openai').
* @param {string} params.modelId - The specific AI model ID used.
* @param {number} params.inputTokens - Number of input tokens.
* @param {number} params.outputTokens - Number of output tokens.
*/
async function logAiUsage({
userId,
commandName,
providerName,
modelId,
inputTokens,
outputTokens,
outputType
}) {
try {
const isMCP = outputType === 'mcp';
const timestamp = new Date().toISOString();
const totalTokens = (inputTokens || 0) + (outputTokens || 0);
// Destructure currency along with costs
const { inputCost, outputCost, currency } = _getCostForModel(
providerName,
modelId
);
const totalCost =
((inputTokens || 0) / 1_000_000) * inputCost +
((outputTokens || 0) / 1_000_000) * outputCost;
const telemetryData = {
timestamp,
userId,
commandName,
modelUsed: modelId, // Consistent field name from requirements
providerName, // Keep provider name for context
inputTokens: inputTokens || 0,
outputTokens: outputTokens || 0,
totalTokens,
totalCost: parseFloat(totalCost.toFixed(6)),
currency // Add currency to the telemetry data
};
if (getDebugFlag()) {
log('info', 'AI Usage Telemetry:', telemetryData);
}
// TODO (Subtask 77.2): Send telemetryData securely to the external endpoint.
return telemetryData;
} catch (error) {
log('error', `Failed to log AI usage telemetry: ${error.message}`, {
error
});
// Don't re-throw; telemetry failure shouldn't block core functionality.
return null;
}
}
export {
generateTextService,
streamTextService,
generateObjectService,
logAiUsage
};

View File

@@ -62,7 +62,8 @@ import {
stopLoadingIndicator,
displayModelConfiguration,
displayAvailableModels,
displayApiKeyStatus
displayApiKeyStatus,
displayAiUsageSummary
} from './ui.js';
import { initializeProject } from '../init.js';
@@ -73,6 +74,11 @@ import {
getApiKeyStatusReport
} from './task-manager/models.js';
import { findProjectRoot } from './utils.js';
import {
isValidTaskStatus,
TASK_STATUS_OPTIONS
} from '../../src/constants/task-status.js';
import { getTaskMasterVersion } from '../../src/utils/getVersion.js';
import {
convertAllRulesToBrandRules,
removeBrandRules,
@@ -494,153 +500,6 @@ function registerCommands(programInstance) {
process.exit(1);
});
// Default help
programInstance.on('--help', function () {
displayHelp();
});
// Add/remove brand rules command
programInstance
.command('rules <action> [brands...]')
.description(
'Add or remove rules for one or more brands (e.g., task-master rules add windsurf roo)'
)
.option(
'-f, --force',
'Skip confirmation prompt when removing rules (dangerous)'
)
.action(async (action, brands, options) => {
const projectDir = process.cwd();
/**
* 'task-master rules setup' action:
*
* Launches an interactive prompt to select which brand rules to apply to the current project.
* This does NOT perform project initialization or ask about shell aliases—only rules selection.
*
* Example usage:
* $ task-master rules setup
*
* Useful for updating/enforcing rules after project creation, or switching brands.
*
* The list of brands is always up-to-date with the available profiles.
*/
if (action === 'setup') {
// Run interactive rules setup ONLY (no project init)
const selectedBrandRules = await runInteractiveRulesSetup();
for (const brand of selectedBrandRules) {
if (!isValidBrand(brand)) {
console.warn(
`Rules profile for brand "${brand}" not found. Valid brands: ${BRAND_NAMES.join(', ')}. Skipping.`
);
continue;
}
const profile = getBrandProfile(brand);
const addResult = convertAllRulesToBrandRules(projectDir, profile);
if (typeof profile.onAddBrandRules === 'function') {
profile.onAddBrandRules(projectDir);
}
console.log(
chalk.green(
`Summary for ${brand}: ${addResult.success} rules added, ${addResult.failed} failed.`
)
);
}
return;
}
if (!brands || brands.length === 0) {
console.error(
'Please specify at least one brand (e.g., windsurf, roo).'
);
process.exit(1);
}
// Support both space- and comma-separated brand lists
const expandedBrands = brands
.flatMap((b) => b.split(',').map((s) => s.trim()))
.filter(Boolean);
if (action === 'remove') {
let confirmed = true;
if (!options.force) {
const ui = await import('./ui.js');
confirmed = await ui.confirmRulesRemove(expandedBrands);
}
if (!confirmed) {
console.log(chalk.yellow('Aborted: No rules were removed.'));
return;
}
}
// (removed duplicate projectDir, brands check, and expandedBrands parsing)
const removalResults = [];
for (const brand of expandedBrands) {
if (!isValidBrand(brand)) {
console.warn(
`Rules profile for brand "${brand}" not found. Valid brands: ${BRAND_NAMES.join(', ')}. Skipping.`
);
continue;
}
const profile = getBrandProfile(brand);
if (action === 'add') {
console.log(chalk.blue(`Adding rules for brand: ${brand}...`));
const addResult = convertAllRulesToBrandRules(projectDir, profile);
if (typeof profile.onAddBrandRules === 'function') {
profile.onAddBrandRules(projectDir);
}
console.log(chalk.blue(`Completed adding rules for brand: ${brand}`));
console.log(
chalk.green(
`Summary for ${brand}: ${addResult.success} rules added, ${addResult.failed} failed.`
)
);
} else if (action === 'remove') {
console.log(chalk.blue(`Removing rules for brand: ${brand}...`));
const result = removeBrandRules(projectDir, profile);
removalResults.push(result);
console.log(chalk.blue(`Completed removal for brand: ${brand}`));
} else {
console.error('Unknown action. Use "add" or "remove".');
process.exit(1);
}
}
// Print summary for removals
if (action === 'remove') {
const successes = removalResults
.filter((r) => r.success)
.map((r) => r.brandName);
const skipped = removalResults
.filter((r) => r.skipped)
.map((r) => r.brandName);
const errors = removalResults.filter(
(r) => r.error && !r.success && !r.skipped
);
if (successes.length > 0) {
console.log(
chalk.green(`Successfully removed rules: ${successes.join(', ')}`)
);
}
if (skipped.length > 0) {
console.log(
chalk.yellow(
`Skipped (default or protected): ${skipped.join(', ')}`
)
);
}
if (errors.length > 0) {
errors.forEach((r) => {
console.log(chalk.red(`Error removing ${r.brandName}: ${r.error}`));
});
}
}
});
// parse-prd command
programInstance
.command('parse-prd')
@@ -665,8 +524,8 @@ function registerCommands(programInstance) {
const outputPath = options.output;
const force = options.force || false;
const append = options.append || false;
let useForce = false;
let useAppend = false;
let useForce = force;
let useAppend = append;
// Helper function to check if tasks.json exists and confirm overwrite
async function confirmOverwriteIfNeeded() {
@@ -694,10 +553,10 @@ function registerCommands(programInstance) {
if (!(await confirmOverwriteIfNeeded())) return;
console.log(chalk.blue(`Generating ${numTasks} tasks...`));
spinner = ora('Parsing PRD and generating tasks...').start();
spinner = ora('Parsing PRD and generating tasks...\n').start();
await parsePRD(defaultPrdPath, outputPath, numTasks, {
useAppend,
useForce
append: useAppend, // Changed key from useAppend to append
force: useForce // Changed key from useForce to force
});
spinner.succeed('Tasks generated successfully!');
return;
@@ -756,10 +615,10 @@ function registerCommands(programInstance) {
console.log(chalk.blue('Appending to existing tasks...'));
}
spinner = ora('Parsing PRD and generating tasks...').start();
spinner = ora('Parsing PRD and generating tasks...\n').start();
await parsePRD(inputFile, outputPath, numTasks, {
append: useAppend,
force: useForce
useAppend: useAppend,
useForce: useForce
});
spinner.succeed('Tasks generated successfully!');
} catch (error) {
@@ -1188,7 +1047,7 @@ function registerCommands(programInstance) {
)
.option(
'-s, --status <status>',
'New status (todo, in-progress, review, done)'
`New status (one of: ${TASK_STATUS_OPTIONS.join(', ')})`
)
.option('-f, --file <file>', 'Path to the tasks file', 'tasks/tasks.json')
.action(async (options) => {
@@ -1201,6 +1060,16 @@ function registerCommands(programInstance) {
process.exit(1);
}
if (!isValidTaskStatus(status)) {
console.error(
chalk.red(
`Error: Invalid status value: ${status}. Use one of: ${TASK_STATUS_OPTIONS.join(', ')}`
)
);
process.exit(1);
}
console.log(
chalk.blue(`Setting status of task(s) ${taskId} to: ${status}`)
);
@@ -1213,10 +1082,16 @@ function registerCommands(programInstance) {
.command('list')
.description('List all tasks')
.option('-f, --file <file>', 'Path to the tasks file', 'tasks/tasks.json')
.option(
'-r, --report <report>',
'Path to the complexity report file',
'scripts/task-complexity-report.json'
)
.option('-s, --status <status>', 'Filter by status')
.option('--with-subtasks', 'Show subtasks for each task')
.action(async (options) => {
const tasksPath = options.file;
const reportPath = options.report;
const statusFilter = options.status;
const withSubtasks = options.withSubtasks || false;
@@ -1228,7 +1103,7 @@ function registerCommands(programInstance) {
console.log(chalk.blue('Including subtasks in listing'));
}
await listTasks(tasksPath, statusFilter, withSubtasks);
await listTasks(tasksPath, statusFilter, reportPath, withSubtasks);
});
// expand command
@@ -1278,12 +1153,6 @@ function registerCommands(programInstance) {
{} // Pass empty context for CLI calls
// outputFormat defaults to 'text' in expandAllTasks for CLI
);
// Optional: Display summary from result
console.log(chalk.green(`Expansion Summary:`));
console.log(chalk.green(` - Attempted: ${result.tasksToExpand}`));
console.log(chalk.green(` - Expanded: ${result.expandedCount}`));
console.log(chalk.yellow(` - Skipped: ${result.skippedCount}`));
console.log(chalk.red(` - Failed: ${result.failedCount}`));
} catch (error) {
console.error(
chalk.red(`Error expanding all tasks: ${error.message}`)
@@ -1413,7 +1282,7 @@ function registerCommands(programInstance) {
// add-task command
programInstance
.command('add-task')
.description('Add a new task using AI or manual input')
.description('Add a new task using AI, optionally providing manual details')
.option('-f, --file <file>', 'Path to the tasks file', 'tasks/tasks.json')
.option(
'-p, --prompt <prompt>',
@@ -1428,10 +1297,6 @@ function registerCommands(programInstance) {
'--details <details>',
'Implementation details (for manual task creation)'
)
.option(
'--test-strategy <testStrategy>',
'Test strategy (for manual task creation)'
)
.option(
'--dependencies <dependencies>',
'Comma-separated list of task IDs this task depends on'
@@ -1458,74 +1323,70 @@ function registerCommands(programInstance) {
process.exit(1);
}
const tasksPath =
options.file ||
path.join(findProjectRoot() || '.', 'tasks', 'tasks.json') || // Ensure tasksPath is also relative to a found root or current dir
'tasks/tasks.json';
// Correctly determine projectRoot
const projectRoot = findProjectRoot();
let manualTaskData = null;
if (isManualCreation) {
manualTaskData = {
title: options.title,
description: options.description,
details: options.details || '',
testStrategy: options.testStrategy || ''
};
// Restore specific logging for manual creation
console.log(
chalk.blue(`Creating task manually with title: "${options.title}"`)
);
} else {
// Restore specific logging for AI creation
console.log(
chalk.blue(`Creating task with AI using prompt: "${options.prompt}"`)
);
}
// Log dependencies and priority if provided (restored)
const dependenciesArray = options.dependencies
? options.dependencies.split(',').map((id) => id.trim())
: [];
if (dependenciesArray.length > 0) {
console.log(
chalk.blue(`Dependencies: [${dependenciesArray.join(', ')}]`)
);
}
if (options.priority) {
console.log(chalk.blue(`Priority: ${options.priority}`));
}
const context = {
projectRoot,
commandName: 'add-task',
outputType: 'cli'
};
try {
// Prepare dependencies if provided
let dependencies = [];
if (options.dependencies) {
dependencies = options.dependencies
.split(',')
.map((id) => parseInt(id.trim(), 10));
}
// Create manual task data if title and description are provided
let manualTaskData = null;
if (isManualCreation) {
manualTaskData = {
title: options.title,
description: options.description,
details: options.details || '',
testStrategy: options.testStrategy || ''
};
console.log(
chalk.blue(`Creating task manually with title: "${options.title}"`)
);
if (dependencies.length > 0) {
console.log(
chalk.blue(`Dependencies: [${dependencies.join(', ')}]`)
);
}
if (options.priority) {
console.log(chalk.blue(`Priority: ${options.priority}`));
}
} else {
console.log(
chalk.blue(
`Creating task with AI using prompt: "${options.prompt}"`
)
);
if (dependencies.length > 0) {
console.log(
chalk.blue(`Dependencies: [${dependencies.join(', ')}]`)
);
}
if (options.priority) {
console.log(chalk.blue(`Priority: ${options.priority}`));
}
}
// Pass mcpLog and session for MCP mode
const newTaskId = await addTask(
options.file,
options.prompt, // Pass prompt (will be null/undefined if not provided)
dependencies,
const { newTaskId, telemetryData } = await addTask(
tasksPath,
options.prompt,
dependenciesArray,
options.priority,
{
// For CLI, session context isn't directly available like MCP
// We don't need to pass session here for CLI API key resolution
// as dotenv loads .env, and utils.resolveEnvVariable checks process.env
},
'text', // outputFormat
manualTaskData, // Pass the potentially created manualTaskData object
options.research || false // Pass the research flag value
context,
'text',
manualTaskData,
options.research
);
console.log(chalk.green(`✓ Added new task #${newTaskId}`));
console.log(chalk.gray('Next: Complete this task or add more tasks'));
// addTask handles detailed CLI success logging AND telemetry display when outputFormat is 'text'
// No need to call displayAiUsageSummary here anymore.
} catch (error) {
console.error(chalk.red(`Error adding task: ${error.message}`));
if (error.stack && getDebugFlag()) {
console.error(error.stack);
if (error.details) {
console.error(chalk.red(error.details));
}
process.exit(1);
}
@@ -1538,9 +1399,15 @@ function registerCommands(programInstance) {
`Show the next task to work on based on dependencies and status${chalk.reset('')}`
)
.option('-f, --file <file>', 'Path to the tasks file', 'tasks/tasks.json')
.option(
'-r, --report <report>',
'Path to the complexity report file',
'scripts/task-complexity-report.json'
)
.action(async (options) => {
const tasksPath = options.file;
await displayNextTask(tasksPath);
const reportPath = options.report;
await displayNextTask(tasksPath, reportPath);
});
// show command
@@ -1553,6 +1420,11 @@ function registerCommands(programInstance) {
.option('-i, --id <id>', 'Task ID to show')
.option('-s, --status <status>', 'Filter subtasks by status') // ADDED status option
.option('-f, --file <file>', 'Path to the tasks file', 'tasks/tasks.json')
.option(
'-r, --report <report>',
'Path to the complexity report file',
'scripts/task-complexity-report.json'
)
.action(async (taskId, options) => {
const idArg = taskId || options.id;
const statusFilter = options.status; // ADDED: Capture status filter
@@ -1563,8 +1435,9 @@ function registerCommands(programInstance) {
}
const tasksPath = options.file;
const reportPath = options.report;
// PASS statusFilter to the display function
await displayTaskById(tasksPath, idArg, statusFilter);
await displayTaskById(tasksPath, idArg, reportPath, statusFilter);
});
// add-dependency command
@@ -1813,6 +1686,7 @@ function registerCommands(programInstance) {
}
} catch (error) {
console.error(chalk.red(`Error: ${error.message}`));
showAddSubtaskHelp();
process.exit(1);
}
})
@@ -2219,7 +2093,7 @@ function registerCommands(programInstance) {
);
// Exit with error if any removals failed
if (successfulRemovals.length === 0) {
if (result.removedTasks.length === 0) {
process.exit(1);
}
}
@@ -2498,6 +2372,148 @@ Examples:
return; // Stop execution here
});
// Add/remove brand rules command
programInstance
.command('rules <action> [brands...]')
.description(
'Add or remove rules for one or more brands (e.g., task-master rules add windsurf roo)'
)
.option(
'-f, --force',
'Skip confirmation prompt when removing rules (dangerous)'
)
.action(async (action, brands, options) => {
const projectDir = process.cwd();
/**
* 'task-master rules setup' action:
*
* Launches an interactive prompt to select which brand rules to apply to the current project.
* This does NOT perform project initialization or ask about shell aliases—only rules selection.
*
* Example usage:
* $ task-master rules setup
*
* Useful for updating/enforcing rules after project creation, or switching brands.
*
* The list of brands is always up-to-date with the available profiles.
*/
if (action === 'setup') {
// Run interactive rules setup ONLY (no project init)
const selectedBrandRules = await runInteractiveRulesSetup();
for (const brand of selectedBrandRules) {
if (!isValidBrand(brand)) {
console.warn(
`Rules profile for brand "${brand}" not found. Valid brands: ${BRAND_NAMES.join(', ')}. Skipping.`
);
continue;
}
const profile = getBrandProfile(brand);
const addResult = convertAllRulesToBrandRules(projectDir, profile);
if (typeof profile.onAddBrandRules === 'function') {
profile.onAddBrandRules(projectDir);
}
console.log(
chalk.green(
`Summary for ${brand}: ${addResult.success} rules added, ${addResult.failed} failed.`
)
);
}
return;
}
if (!brands || brands.length === 0) {
console.error(
'Please specify at least one brand (e.g., windsurf, roo).'
);
process.exit(1);
}
// Support both space- and comma-separated brand lists
const expandedBrands = brands
.flatMap((b) => b.split(',').map((s) => s.trim()))
.filter(Boolean);
if (action === 'remove') {
let confirmed = true;
if (!options.force) {
const ui = await import('./ui.js');
confirmed = await ui.confirmRulesRemove(expandedBrands);
}
if (!confirmed) {
console.log(chalk.yellow('Aborted: No rules were removed.'));
return;
}
}
// (removed duplicate projectDir, brands check, and expandedBrands parsing)
const removalResults = [];
for (const brand of expandedBrands) {
if (!isValidBrand(brand)) {
console.warn(
`Rules profile for brand "${brand}" not found. Valid brands: ${BRAND_NAMES.join(', ')}. Skipping.`
);
continue;
}
const profile = getBrandProfile(brand);
if (action === 'add') {
console.log(chalk.blue(`Adding rules for brand: ${brand}...`));
const addResult = convertAllRulesToBrandRules(projectDir, profile);
if (typeof profile.onAddBrandRules === 'function') {
profile.onAddBrandRules(projectDir);
}
console.log(chalk.blue(`Completed adding rules for brand: ${brand}`));
console.log(
chalk.green(
`Summary for ${brand}: ${addResult.success} rules added, ${addResult.failed} failed.`
)
);
} else if (action === 'remove') {
console.log(chalk.blue(`Removing rules for brand: ${brand}...`));
const result = removeBrandRules(projectDir, profile);
removalResults.push(result);
console.log(chalk.blue(`Completed removal for brand: ${brand}`));
} else {
console.error('Unknown action. Use "add" or "remove".');
process.exit(1);
}
}
// Print summary for removals
if (action === 'remove') {
const successes = removalResults
.filter((r) => r.success)
.map((r) => r.brandName);
const skipped = removalResults
.filter((r) => r.skipped)
.map((r) => r.brandName);
const errors = removalResults.filter(
(r) => r.error && !r.success && !r.skipped
);
if (successes.length > 0) {
console.log(
chalk.green(`Successfully removed rules: ${successes.join(', ')}`)
);
}
if (skipped.length > 0) {
console.log(
chalk.yellow(
`Skipped (default or protected): ${skipped.join(', ')}`
)
);
}
if (errors.length > 0) {
errors.forEach((r) => {
console.log(chalk.red(`Error removing ${r.brandName}: ${r.error}`));
});
}
}
});
return programInstance;
}
@@ -2530,14 +2546,7 @@ function setupCLI() {
return 'unknown'; // Default fallback if package.json fails
})
.helpOption('-h, --help', 'Display help')
.addHelpCommand(false) // Disable default help command
.on('--help', () => {
displayHelp(); // Use your custom help display instead
})
.on('-h', () => {
displayHelp();
process.exit(0);
});
.addHelpCommand(false); // Disable default help command
// Modify the help option to use your custom display
programInstance.helpInformation = () => {
@@ -2557,28 +2566,7 @@ function setupCLI() {
*/
async function checkForUpdate() {
// Get current version from package.json ONLY
let currentVersion = 'unknown'; // Initialize with a default
try {
// Try to get the version from the installed package (if applicable) or current dir
let packageJsonPath = path.join(
process.cwd(),
'node_modules',
'task-master-ai',
'package.json'
);
// Fallback to current directory package.json if not found in node_modules
if (!fs.existsSync(packageJsonPath)) {
packageJsonPath = path.join(process.cwd(), 'package.json');
}
if (fs.existsSync(packageJsonPath)) {
const packageJson = JSON.parse(fs.readFileSync(packageJsonPath, 'utf8'));
currentVersion = packageJson.version;
}
} catch (error) {
// Silently fail and use default
log('debug', `Error reading current package version: ${error.message}`);
}
const currentVersion = getTaskMasterVersion();
return new Promise((resolve) => {
// Get the latest version from npm registry

View File

@@ -669,6 +669,34 @@ function isConfigFilePresent(explicitRoot = null) {
return fs.existsSync(configPath);
}
/**
* Gets the user ID from the configuration.
* @param {string|null} explicitRoot - Optional explicit path to the project root.
* @returns {string|null} The user ID or null if not found.
*/
function getUserId(explicitRoot = null) {
const config = getConfig(explicitRoot);
if (!config.global) {
config.global = {}; // Ensure global object exists
}
if (!config.global.userId) {
config.global.userId = '1234567890';
// Attempt to write the updated config.
// It's important that writeConfig correctly resolves the path
// using explicitRoot, similar to how getConfig does.
const success = writeConfig(config, explicitRoot);
if (!success) {
// Log an error or handle the failure to write,
// though for now, we'll proceed with the in-memory default.
log(
'warning',
'Failed to write updated configuration with new userId. Please let the developers know.'
);
}
}
return config.global.userId;
}
/**
* Gets a list of all provider names defined in the MODEL_MAP.
* @returns {string[]} An array of provider names.
@@ -677,12 +705,19 @@ function getAllProviders() {
return Object.keys(MODEL_MAP || {});
}
function getBaseUrlForRole(role, explicitRoot = null) {
const roleConfig = getModelConfigForRole(role, explicitRoot);
return roleConfig && typeof roleConfig.baseUrl === 'string'
? roleConfig.baseUrl
: undefined;
}
export {
// Core config access
getConfig,
writeConfig,
ConfigurationError, // Export custom error type
isConfigFilePresent, // Add the new function export
ConfigurationError,
isConfigFilePresent,
// Validation
validateProvider,
@@ -704,6 +739,7 @@ export {
getFallbackModelId,
getFallbackMaxTokens,
getFallbackTemperature,
getBaseUrlForRole,
// Global setting getters (No env var overrides)
getLogLevel,
@@ -714,7 +750,7 @@ export {
getProjectName,
getOllamaBaseUrl,
getParametersForRole,
getUserId,
// API Key Checkers (still relevant)
isApiKeySet,
getMcpApiKeyStatus,

View File

@@ -99,34 +99,39 @@
],
"google": [
{
"id": "gemini-2.5-pro-exp-03-25",
"id": "gemini-2.5-pro-preview-05-06",
"swe_score": 0.638,
"cost_per_1m_tokens": null,
"allowed_roles": ["main", "fallback"]
"allowed_roles": ["main", "fallback"],
"max_tokens": 1048000
},
{
"id": "gemini-2.5-pro-preview-03-25",
"swe_score": 0.638,
"cost_per_1m_tokens": null,
"allowed_roles": ["main", "fallback"],
"max_tokens": 1048000
},
{
"id": "gemini-2.5-flash-preview-04-17",
"swe_score": 0,
"cost_per_1m_tokens": null,
"allowed_roles": ["main", "fallback"]
"allowed_roles": ["main", "fallback"],
"max_tokens": 1048000
},
{
"id": "gemini-2.0-flash",
"swe_score": 0.754,
"cost_per_1m_tokens": { "input": 0.15, "output": 0.6 },
"allowed_roles": ["main", "fallback"]
"allowed_roles": ["main", "fallback"],
"max_tokens": 1048000
},
{
"id": "gemini-2.0-flash-thinking-experimental",
"swe_score": 0.754,
"cost_per_1m_tokens": { "input": 0.15, "output": 0.6 },
"allowed_roles": ["main", "fallback"]
},
{
"id": "gemini-2.0-pro",
"id": "gemini-2.0-flash-lite",
"swe_score": 0,
"cost_per_1m_tokens": null,
"allowed_roles": ["main", "fallback"]
"allowed_roles": ["main", "fallback"],
"max_tokens": 1048000
}
],
"perplexity": [

View File

@@ -23,7 +23,7 @@ import updateSubtaskById from './task-manager/update-subtask-by-id.js';
import removeTask from './task-manager/remove-task.js';
import taskExists from './task-manager/task-exists.js';
import isTaskDependentOn from './task-manager/is-task-dependent.js';
import { readComplexityReport } from './utils.js';
// Export task manager functions
export {
parsePRD,
@@ -45,5 +45,6 @@ export {
removeTask,
findTaskById,
taskExists,
isTaskDependentOn
isTaskDependentOn,
readComplexityReport
};

View File

@@ -8,7 +8,8 @@ import {
displayBanner,
getStatusWithColor,
startLoadingIndicator,
stopLoadingIndicator
stopLoadingIndicator,
displayAiUsageSummary
} from '../ui.js';
import { readJSON, writeJSON, log as consoleLog, truncate } from '../utils.js';
import { generateObjectService } from '../ai-services-unified.js';
@@ -44,7 +45,9 @@ const AiTaskDataSchema = z.object({
* @param {boolean} useResearch - Whether to use the research model (passed to unified service)
* @param {Object} context - Context object containing session and potentially projectRoot
* @param {string} [context.projectRoot] - Project root path (for MCP/env fallback)
* @returns {number} The new task ID
* @param {string} [context.commandName] - The name of the command being executed (for telemetry)
* @param {string} [context.outputType] - The output type ('cli' or 'mcp', for telemetry)
* @returns {Promise<object>} An object containing newTaskId and telemetryData
*/
async function addTask(
tasksPath,
@@ -56,7 +59,7 @@ async function addTask(
manualTaskData = null,
useResearch = false
) {
const { session, mcpLog, projectRoot } = context;
const { session, mcpLog, projectRoot, commandName, outputType } = context;
const isMCP = !!mcpLog;
// Create a consistent logFn object regardless of context
@@ -78,6 +81,7 @@ async function addTask(
);
let loadingIndicator = null;
let aiServiceResponse = null; // To store the full response from AI service
// Create custom reporter that checks for MCP log
const report = (message, level = 'info') => {
@@ -89,20 +93,6 @@ async function addTask(
};
try {
// Only display banner and UI elements for text output (CLI)
if (outputFormat === 'text') {
displayBanner();
console.log(
boxen(chalk.white.bold(`Creating New Task`), {
padding: 1,
borderColor: 'blue',
borderStyle: 'round',
margin: { top: 1, bottom: 1 }
})
);
}
// Read the existing tasks
const data = readJSON(tasksPath);
if (!data || !data.tasks) {
@@ -169,7 +159,7 @@ async function addTask(
} else {
report('DEBUG: Taking AI task generation path.', 'debug');
// --- Refactored AI Interaction ---
report('Generating task data with AI...', 'info');
report(`Generating task data with AI with prompt:\n${prompt}`, 'info');
// Create context string for task creation prompt
let contextTasks = '';
@@ -229,29 +219,51 @@ async function addTask(
// Start the loading indicator - only for text mode
if (outputFormat === 'text') {
loadingIndicator = startLoadingIndicator(
`Generating new task with ${useResearch ? 'Research' : 'Main'} AI...`
`Generating new task with ${useResearch ? 'Research' : 'Main'} AI...\n`
);
}
try {
// Determine the service role based on the useResearch flag
const serviceRole = useResearch ? 'research' : 'main';
report('DEBUG: Calling generateObjectService...', 'debug');
// Call the unified AI service
const aiGeneratedTaskData = await generateObjectService({
role: serviceRole, // <-- Use the determined role
session: session, // Pass session for API key resolution
projectRoot: projectRoot, // <<< Pass projectRoot here
schema: AiTaskDataSchema, // Pass the Zod schema
objectName: 'newTaskData', // Name for the object
aiServiceResponse = await generateObjectService({
// Capture the full response
role: serviceRole,
session: session,
projectRoot: projectRoot,
schema: AiTaskDataSchema,
objectName: 'newTaskData',
systemPrompt: systemPrompt,
prompt: userPrompt
prompt: userPrompt,
commandName: commandName || 'add-task', // Use passed commandName or default
outputType: outputType || (isMCP ? 'mcp' : 'cli') // Use passed outputType or derive
});
report('DEBUG: generateObjectService returned successfully.', 'debug');
if (!aiServiceResponse || !aiServiceResponse.mainResult) {
throw new Error(
'AI service did not return the expected object structure.'
);
}
// Prefer mainResult if it looks like a valid task object, otherwise try mainResult.object
if (
aiServiceResponse.mainResult.title &&
aiServiceResponse.mainResult.description
) {
taskData = aiServiceResponse.mainResult;
} else if (
aiServiceResponse.mainResult.object &&
aiServiceResponse.mainResult.object.title &&
aiServiceResponse.mainResult.object.description
) {
taskData = aiServiceResponse.mainResult.object;
} else {
throw new Error('AI service did not return a valid task object.');
}
report('Successfully generated task data from AI.', 'success');
taskData = aiGeneratedTaskData; // Assign the validated object
} catch (error) {
report(
`DEBUG: generateObjectService caught error: ${error.message}`,
@@ -362,11 +374,25 @@ async function addTask(
{ padding: 1, borderColor: 'green', borderStyle: 'round' }
)
);
// Display AI Usage Summary if telemetryData is available
if (
aiServiceResponse &&
aiServiceResponse.telemetryData &&
(outputType === 'cli' || outputType === 'text')
) {
displayAiUsageSummary(aiServiceResponse.telemetryData, 'cli');
}
}
// Return the new task ID
report(`DEBUG: Returning new task ID: ${newTaskId}`, 'debug');
return newTaskId;
report(
`DEBUG: Returning new task ID: ${newTaskId} and telemetry.`,
'debug'
);
return {
newTaskId: newTaskId,
telemetryData: aiServiceResponse ? aiServiceResponse.telemetryData : null
};
} catch (error) {
// Stop any loading indicator on error
if (loadingIndicator) {

View File

@@ -4,7 +4,11 @@ import readline from 'readline';
import { log, readJSON, writeJSON, isSilentMode } from '../utils.js';
import { startLoadingIndicator, stopLoadingIndicator } from '../ui.js';
import {
startLoadingIndicator,
stopLoadingIndicator,
displayAiUsageSummary
} from '../ui.js';
import { generateTextService } from '../ai-services-unified.js';
@@ -196,35 +200,32 @@ async function analyzeTaskComplexity(options, context = {}) {
}
const prompt = generateInternalComplexityAnalysisPrompt(tasksData);
// System prompt remains simple for text generation
const systemPrompt =
'You are an expert software architect and project manager analyzing task complexity. Respond only with the requested valid JSON array.';
let loadingIndicator = null;
if (outputFormat === 'text') {
loadingIndicator = startLoadingIndicator('Calling AI service...');
loadingIndicator = startLoadingIndicator(
`${useResearch ? 'Researching' : 'Analyzing'} the complexity of your tasks with AI...\n`
);
}
let fullResponse = ''; // To store the raw text response
let aiServiceResponse = null;
let complexityAnalysis = null;
try {
const role = useResearch ? 'research' : 'main';
reportLog(`Using AI service with role: ${role}`, 'info');
fullResponse = await generateTextService({
aiServiceResponse = await generateTextService({
prompt,
systemPrompt,
role,
session,
projectRoot
projectRoot,
commandName: 'analyze-complexity',
outputType: mcpLog ? 'mcp' : 'cli'
});
reportLog(
'Successfully received text response via AI service',
'success'
);
// --- Stop Loading Indicator (Unchanged) ---
if (loadingIndicator) {
stopLoadingIndicator(loadingIndicator);
loadingIndicator = null;
@@ -236,26 +237,18 @@ async function analyzeTaskComplexity(options, context = {}) {
chalk.green('AI service call complete. Parsing response...')
);
}
// --- End Stop Loading Indicator ---
// --- Re-introduce Manual JSON Parsing & Cleanup ---
reportLog(`Parsing complexity analysis from text response...`, 'info');
let complexityAnalysis;
try {
let cleanedResponse = fullResponse;
// Basic trim first
let cleanedResponse = aiServiceResponse.mainResult;
cleanedResponse = cleanedResponse.trim();
// Remove potential markdown code block fences
const codeBlockMatch = cleanedResponse.match(
/```(?:json)?\s*([\s\S]*?)\s*```/
);
if (codeBlockMatch) {
cleanedResponse = codeBlockMatch[1].trim(); // Trim content inside block
reportLog('Extracted JSON from code block', 'info');
cleanedResponse = codeBlockMatch[1].trim();
} else {
// If no code block, ensure it starts with '[' and ends with ']'
// This is less robust but a common fallback
const firstBracket = cleanedResponse.indexOf('[');
const lastBracket = cleanedResponse.lastIndexOf(']');
if (firstBracket !== -1 && lastBracket > firstBracket) {
@@ -263,13 +256,11 @@ async function analyzeTaskComplexity(options, context = {}) {
firstBracket,
lastBracket + 1
);
reportLog('Extracted content between first [ and last ]', 'info');
} else {
reportLog(
'Warning: Response does not appear to be a JSON array.',
'warn'
);
// Keep going, maybe JSON.parse can handle it or will fail informatively
}
}
@@ -283,48 +274,23 @@ async function analyzeTaskComplexity(options, context = {}) {
);
}
try {
complexityAnalysis = JSON.parse(cleanedResponse);
} catch (jsonError) {
reportLog(
'Initial JSON parsing failed. Raw response might be malformed.',
'error'
);
reportLog(`Original JSON Error: ${jsonError.message}`, 'error');
if (outputFormat === 'text' && getDebugFlag(session)) {
console.log(chalk.red('--- Start Raw Malformed Response ---'));
console.log(chalk.gray(fullResponse));
console.log(chalk.red('--- End Raw Malformed Response ---'));
}
// Re-throw the specific JSON parsing error
throw new Error(
`Failed to parse JSON response: ${jsonError.message}`
);
}
// Ensure it's an array after parsing
if (!Array.isArray(complexityAnalysis)) {
throw new Error('Parsed response is not a valid JSON array.');
}
} catch (error) {
// Catch errors specifically from the parsing/cleanup block
if (loadingIndicator) stopLoadingIndicator(loadingIndicator); // Ensure indicator stops
complexityAnalysis = JSON.parse(cleanedResponse);
} catch (parseError) {
if (loadingIndicator) stopLoadingIndicator(loadingIndicator);
reportLog(
`Error parsing complexity analysis JSON: ${error.message}`,
`Error parsing complexity analysis JSON: ${parseError.message}`,
'error'
);
if (outputFormat === 'text') {
console.error(
chalk.red(
`Error parsing complexity analysis JSON: ${error.message}`
`Error parsing complexity analysis JSON: ${parseError.message}`
)
);
}
throw error; // Re-throw parsing error
throw parseError;
}
// --- End Manual JSON Parsing & Cleanup ---
// --- Post-processing (Missing Task Check) - (Unchanged) ---
const taskIds = tasksData.tasks.map((t) => t.id);
const analysisTaskIds = complexityAnalysis.map((a) => a.taskId);
const missingTaskIds = taskIds.filter(
@@ -359,10 +325,8 @@ async function analyzeTaskComplexity(options, context = {}) {
}
}
}
// --- End Post-processing ---
// --- Report Creation & Writing (Unchanged) ---
const finalReport = {
const report = {
meta: {
generatedAt: new Date().toISOString(),
tasksAnalyzed: tasksData.tasks.length,
@@ -373,15 +337,13 @@ async function analyzeTaskComplexity(options, context = {}) {
complexityAnalysis: complexityAnalysis
};
reportLog(`Writing complexity report to ${outputPath}...`, 'info');
writeJSON(outputPath, finalReport);
writeJSON(outputPath, report);
reportLog(
`Task complexity analysis complete. Report written to ${outputPath}`,
'success'
);
// --- End Report Creation & Writing ---
// --- Display CLI Summary (Unchanged) ---
if (outputFormat === 'text') {
console.log(
chalk.green(
@@ -435,23 +397,28 @@ async function analyzeTaskComplexity(options, context = {}) {
if (getDebugFlag(session)) {
console.debug(
chalk.gray(
`Final analysis object: ${JSON.stringify(finalReport, null, 2)}`
`Final analysis object: ${JSON.stringify(report, null, 2)}`
)
);
}
}
// --- End Display CLI Summary ---
return finalReport;
} catch (error) {
// Catches errors from generateTextService call
if (aiServiceResponse.telemetryData) {
displayAiUsageSummary(aiServiceResponse.telemetryData, 'cli');
}
}
return {
report: report,
telemetryData: aiServiceResponse?.telemetryData
};
} catch (aiError) {
if (loadingIndicator) stopLoadingIndicator(loadingIndicator);
reportLog(`Error during AI service call: ${error.message}`, 'error');
reportLog(`Error during AI service call: ${aiError.message}`, 'error');
if (outputFormat === 'text') {
console.error(
chalk.red(`Error during AI service call: ${error.message}`)
chalk.red(`Error during AI service call: ${aiError.message}`)
);
if (error.message.includes('API key')) {
if (aiError.message.includes('API key')) {
console.log(
chalk.yellow(
'\nPlease ensure your API keys are correctly configured in .env or ~/.taskmaster/.env'
@@ -462,10 +429,9 @@ async function analyzeTaskComplexity(options, context = {}) {
);
}
}
throw error; // Re-throw AI service error
throw aiError;
}
} catch (error) {
// Catches general errors (file read, etc.)
reportLog(`Error analyzing task complexity: ${error.message}`, 'error');
if (outputFormat === 'text') {
console.error(

View File

@@ -1,7 +1,14 @@
import { log, readJSON, isSilentMode } from '../utils.js';
import { startLoadingIndicator, stopLoadingIndicator } from '../ui.js';
import {
startLoadingIndicator,
stopLoadingIndicator,
displayAiUsageSummary
} from '../ui.js';
import expandTask from './expand-task.js';
import { getDebugFlag } from '../config-manager.js';
import { aggregateTelemetry } from '../utils.js';
import chalk from 'chalk';
import boxen from 'boxen';
/**
* Expand all eligible pending or in-progress tasks using the expandTask function.
@@ -14,7 +21,7 @@ import { getDebugFlag } from '../config-manager.js';
* @param {Object} [context.session] - Session object from MCP.
* @param {Object} [context.mcpLog] - MCP logger object.
* @param {string} [outputFormat='text'] - Output format ('text' or 'json'). MCP calls should use 'json'.
* @returns {Promise<{success: boolean, expandedCount: number, failedCount: number, skippedCount: number, tasksToExpand: number, message?: string}>} - Result summary.
* @returns {Promise<{success: boolean, expandedCount: number, failedCount: number, skippedCount: number, tasksToExpand: number, telemetryData: Array<Object>}>} - Result summary.
*/
async function expandAllTasks(
tasksPath,
@@ -51,8 +58,8 @@ async function expandAllTasks(
let loadingIndicator = null;
let expandedCount = 0;
let failedCount = 0;
// No skipped count needed now as the filter handles it upfront
let tasksToExpandCount = 0; // Renamed for clarity
let tasksToExpandCount = 0;
const allTelemetryData = []; // Still collect individual data first
if (!isMCPCall && outputFormat === 'text') {
loadingIndicator = startLoadingIndicator(
@@ -90,6 +97,7 @@ async function expandAllTasks(
failedCount: 0,
skippedCount: 0,
tasksToExpand: 0,
telemetryData: allTelemetryData,
message: 'No tasks eligible for expansion.'
};
// --- End Fix ---
@@ -97,19 +105,6 @@ async function expandAllTasks(
// Iterate over the already filtered tasks
for (const task of tasksToExpand) {
// --- Remove Redundant Check ---
// The check below is no longer needed as the initial filter handles it
/*
if (task.subtasks && task.subtasks.length > 0 && !force) {
logger.info(
`Skipping task ${task.id}: Already has subtasks. Use --force to overwrite.`
);
skippedCount++;
continue;
}
*/
// --- End Removed Redundant Check ---
// Start indicator for individual task expansion in CLI mode
let taskIndicator = null;
if (!isMCPCall && outputFormat === 'text') {
@@ -117,17 +112,23 @@ async function expandAllTasks(
}
try {
// Call the refactored expandTask function
await expandTask(
// Call the refactored expandTask function AND capture result
const result = await expandTask(
tasksPath,
task.id,
numSubtasks, // Pass numSubtasks, expandTask handles defaults/complexity
numSubtasks,
useResearch,
additionalContext,
context, // Pass the whole context object { session, mcpLog }
force // Pass the force flag down
force
);
expandedCount++;
// Collect individual telemetry data
if (result && result.telemetryData) {
allTelemetryData.push(result.telemetryData);
}
if (taskIndicator) {
stopLoadingIndicator(taskIndicator, `Task ${task.id} expanded.`);
}
@@ -146,18 +147,48 @@ async function expandAllTasks(
}
}
// Log final summary (removed skipped count from message)
// --- AGGREGATION AND DISPLAY ---
logger.info(
`Expansion complete: ${expandedCount} expanded, ${failedCount} failed.`
);
// Return summary (skippedCount is now 0) - Add success: true here as well for consistency
// Aggregate the collected telemetry data
const aggregatedTelemetryData = aggregateTelemetry(
allTelemetryData,
'expand-all-tasks'
);
if (outputFormat === 'text') {
const summaryContent =
`${chalk.white.bold('Expansion Summary:')}\n\n` +
`${chalk.cyan('-')} Attempted: ${chalk.bold(tasksToExpandCount)}\n` +
`${chalk.green('-')} Expanded: ${chalk.bold(expandedCount)}\n` +
// Skipped count is always 0 now due to pre-filtering
`${chalk.gray('-')} Skipped: ${chalk.bold(0)}\n` +
`${chalk.red('-')} Failed: ${chalk.bold(failedCount)}`;
console.log(
boxen(summaryContent, {
padding: 1,
margin: { top: 1 },
borderColor: failedCount > 0 ? 'red' : 'green', // Red if failures, green otherwise
borderStyle: 'round'
})
);
}
if (outputFormat === 'text' && aggregatedTelemetryData) {
displayAiUsageSummary(aggregatedTelemetryData, 'cli');
}
// Return summary including the AGGREGATED telemetry data
return {
success: true, // Indicate overall success
success: true,
expandedCount,
failedCount,
skippedCount: 0,
tasksToExpand: tasksToExpandCount
tasksToExpand: tasksToExpandCount,
telemetryData: aggregatedTelemetryData
};
} catch (error) {
if (loadingIndicator)

View File

@@ -4,7 +4,11 @@ import { z } from 'zod';
import { log, readJSON, writeJSON, isSilentMode } from '../utils.js';
import { startLoadingIndicator, stopLoadingIndicator } from '../ui.js';
import {
startLoadingIndicator,
stopLoadingIndicator,
displayAiUsageSummary
} from '../ui.js';
import { generateTextService } from '../ai-services-unified.js';
@@ -142,7 +146,7 @@ function generateResearchUserPrompt(
"id": <number>, // Sequential ID starting from ${nextSubtaskId}
"title": "<string>",
"description": "<string>",
"dependencies": [<number>], // e.g., [${nextSubtaskId + 1}]
"dependencies": [<number>], // e.g., [${nextSubtaskId + 1}]. If no dependencies, use an empty array [].
"details": "<string>",
"testStrategy": "<string>" // Optional
},
@@ -162,6 +166,8 @@ ${contextPrompt}
CRITICAL: Respond ONLY with a valid JSON object containing a single key "subtasks". The value must be an array of the generated subtasks, strictly matching this structure:
${schemaDescription}
Important: For the 'dependencies' field, if a subtask has no dependencies, you MUST use an empty array, for example: "dependencies": []. Do not use null or omit the field.
Do not include ANY explanatory text, markdown, or code block markers. Just the JSON object.`;
}
@@ -182,77 +188,153 @@ function parseSubtasksFromText(
parentTaskId,
logger
) {
logger.info('Attempting to parse subtasks object from text response...');
if (!text || text.trim() === '') {
throw new Error('AI response text is empty.');
if (typeof text !== 'string') {
logger.error(
`AI response text is not a string. Received type: ${typeof text}, Value: ${text}`
);
throw new Error('AI response text is not a string.');
}
let cleanedResponse = text.trim();
const originalResponseForDebug = cleanedResponse;
if (!text || text.trim() === '') {
throw new Error('AI response text is empty after trimming.');
}
// 1. Extract from Markdown code block first
const codeBlockMatch = cleanedResponse.match(
/```(?:json)?\s*([\s\S]*?)\s*```/
const originalTrimmedResponse = text.trim(); // Store the original trimmed response
let jsonToParse = originalTrimmedResponse; // Initialize jsonToParse with it
logger.debug(
`Original AI Response for parsing (full length: ${jsonToParse.length}): ${jsonToParse.substring(0, 1000)}...`
);
if (codeBlockMatch) {
cleanedResponse = codeBlockMatch[1].trim();
logger.info('Extracted JSON content from Markdown code block.');
} else {
// 2. If no code block, find first '{' and last '}' for the object
const firstBrace = cleanedResponse.indexOf('{');
const lastBrace = cleanedResponse.lastIndexOf('}');
if (firstBrace !== -1 && lastBrace > firstBrace) {
cleanedResponse = cleanedResponse.substring(firstBrace, lastBrace + 1);
logger.info('Extracted content between first { and last }.');
// --- Pre-emptive cleanup for known AI JSON issues ---
// Fix for "dependencies": , or "dependencies":,
if (jsonToParse.includes('"dependencies":')) {
const malformedPattern = /"dependencies":\s*,/g;
if (malformedPattern.test(jsonToParse)) {
logger.warn('Attempting to fix malformed "dependencies": , issue.');
jsonToParse = jsonToParse.replace(
malformedPattern,
'"dependencies": [],'
);
logger.debug(
`JSON after fixing "dependencies": ${jsonToParse.substring(0, 500)}...`
);
}
}
// --- End pre-emptive cleanup ---
let parsedObject;
let primaryParseAttemptFailed = false;
// --- Attempt 1: Simple Parse (with optional Markdown cleanup) ---
logger.debug('Attempting simple parse...');
try {
// Check for markdown code block
const codeBlockMatch = jsonToParse.match(/```(?:json)?\s*([\s\S]*?)\s*```/);
let contentToParseDirectly = jsonToParse;
if (codeBlockMatch && codeBlockMatch[1]) {
contentToParseDirectly = codeBlockMatch[1].trim();
logger.debug('Simple parse: Extracted content from markdown code block.');
} else {
logger.debug(
'Simple parse: No markdown code block found, using trimmed original.'
);
}
parsedObject = JSON.parse(contentToParseDirectly);
logger.debug('Simple parse successful!');
// Quick check if it looks like our target object
if (
!parsedObject ||
typeof parsedObject !== 'object' ||
!Array.isArray(parsedObject.subtasks)
) {
logger.warn(
'Response does not appear to contain a JSON object structure. Parsing raw response.'
'Simple parse succeeded, but result is not the expected {"subtasks": []} structure. Will proceed to advanced extraction.'
);
primaryParseAttemptFailed = true;
parsedObject = null; // Reset parsedObject so we enter the advanced logic
}
// If it IS the correct structure, we'll skip advanced extraction.
} catch (e) {
logger.warn(
`Simple parse failed: ${e.message}. Proceeding to advanced extraction logic.`
);
primaryParseAttemptFailed = true;
// jsonToParse is already originalTrimmedResponse if simple parse failed before modifying it for markdown
}
// --- Attempt 2: Advanced Extraction (if simple parse failed or produced wrong structure) ---
if (primaryParseAttemptFailed || !parsedObject) {
// Ensure we try advanced if simple parse gave wrong structure
logger.debug('Attempting advanced extraction logic...');
// Reset jsonToParse to the original full trimmed response for advanced logic
jsonToParse = originalTrimmedResponse;
// (Insert the more complex extraction logic here - the one we worked on with:
// - targetPattern = '{"subtasks":';
// - careful brace counting for that targetPattern
// - fallbacks to last '{' and '}' if targetPattern logic fails)
// This was the logic from my previous message. Let's assume it's here.
// This block should ultimately set `jsonToParse` to the best candidate string.
// Example snippet of that advanced logic's start:
const targetPattern = '{"subtasks":';
const patternStartIndex = jsonToParse.indexOf(targetPattern);
if (patternStartIndex !== -1) {
let openBraces = 0;
let firstBraceFound = false;
let extractedJsonBlock = '';
// ... (loop for brace counting as before) ...
// ... (if successful, jsonToParse = extractedJsonBlock) ...
// ... (if that fails, fallbacks as before) ...
} else {
// ... (fallback to last '{' and '}' if targetPattern not found) ...
}
// End of advanced logic excerpt
logger.debug(
`Advanced extraction: JSON string that will be parsed: ${jsonToParse.substring(0, 500)}...`
);
try {
parsedObject = JSON.parse(jsonToParse);
logger.debug('Advanced extraction parse successful!');
} catch (parseError) {
logger.error(
`Advanced extraction: Failed to parse JSON object: ${parseError.message}`
);
logger.error(
`Advanced extraction: Problematic JSON string for parse (first 500 chars): ${jsonToParse.substring(0, 500)}`
);
throw new Error( // Re-throw a more specific error if advanced also fails
`Failed to parse JSON response object after both simple and advanced attempts: ${parseError.message}`
);
}
}
// 3. Attempt to parse the object
let parsedObject;
try {
parsedObject = JSON.parse(cleanedResponse);
} catch (parseError) {
logger.error(`Failed to parse JSON object: ${parseError.message}`);
logger.error(
`Problematic JSON string (first 500 chars): ${cleanedResponse.substring(0, 500)}`
);
logger.error(
`Original Raw Response (first 500 chars): ${originalResponseForDebug.substring(0, 500)}`
);
throw new Error(
`Failed to parse JSON response object: ${parseError.message}`
);
}
// 4. Validate the object structure and extract the subtasks array
// --- Validation (applies to successfully parsedObject from either attempt) ---
if (
!parsedObject ||
typeof parsedObject !== 'object' ||
!Array.isArray(parsedObject.subtasks)
) {
logger.error(
`Parsed content is not an object or missing 'subtasks' array. Content: ${JSON.stringify(parsedObject).substring(0, 200)}`
`Final parsed content is not an object or missing 'subtasks' array. Content: ${JSON.stringify(parsedObject).substring(0, 200)}`
);
throw new Error(
'Parsed AI response is not a valid object containing a "subtasks" array.'
'Parsed AI response is not a valid object containing a "subtasks" array after all attempts.'
);
}
const parsedSubtasks = parsedObject.subtasks; // Extract the array
const parsedSubtasks = parsedObject.subtasks;
logger.info(
`Successfully parsed ${parsedSubtasks.length} potential subtasks from the object.`
);
if (expectedCount && parsedSubtasks.length !== expectedCount) {
logger.warn(
`Expected ${expectedCount} subtasks, but parsed ${parsedSubtasks.length}.`
);
}
// 5. Validate and Normalize each subtask using Zod schema
let currentId = startId;
const validatedSubtasks = [];
const validationErrors = [];
@@ -260,22 +342,21 @@ function parseSubtasksFromText(
for (const rawSubtask of parsedSubtasks) {
const correctedSubtask = {
...rawSubtask,
id: currentId, // Enforce sequential ID
id: currentId,
dependencies: Array.isArray(rawSubtask.dependencies)
? rawSubtask.dependencies
.map((dep) => (typeof dep === 'string' ? parseInt(dep, 10) : dep))
.filter(
(depId) => !isNaN(depId) && depId >= startId && depId < currentId
) // Ensure deps are numbers, valid range
)
: [],
status: 'pending' // Enforce pending status
// parentTaskId can be added if needed: parentTaskId: parentTaskId
status: 'pending'
};
const result = subtaskSchema.safeParse(correctedSubtask);
if (result.success) {
validatedSubtasks.push(result.data); // Add the validated data
validatedSubtasks.push(result.data);
} else {
logger.warn(
`Subtask validation failed for raw data: ${JSON.stringify(rawSubtask).substring(0, 100)}...`
@@ -285,18 +366,14 @@ function parseSubtasksFromText(
logger.warn(errorMessage);
validationErrors.push(`Subtask ${currentId}: ${errorMessage}`);
});
// Optionally, decide whether to include partially valid tasks or skip them
// For now, we'll skip invalid ones
}
currentId++; // Increment ID for the next *potential* subtask
currentId++;
}
if (validationErrors.length > 0) {
logger.error(
`Found ${validationErrors.length} validation errors in the generated subtasks.`
);
// Optionally throw an error here if strict validation is required
// throw new Error(`Subtask validation failed:\n${validationErrors.join('\n')}`);
logger.warn('Proceeding with only the successfully validated subtasks.');
}
@@ -305,8 +382,6 @@ function parseSubtasksFromText(
'AI response contained potential subtasks, but none passed validation.'
);
}
// Ensure we don't return more than expected, preferring validated ones
return validatedSubtasks.slice(0, expectedCount || validatedSubtasks.length);
}
@@ -336,9 +411,13 @@ async function expandTask(
context = {},
force = false
) {
const { session, mcpLog } = context;
const { session, mcpLog, projectRoot: contextProjectRoot } = context;
const outputFormat = mcpLog ? 'json' : 'text';
// Determine projectRoot: Use from context if available, otherwise derive from tasksPath
const projectRoot =
contextProjectRoot || path.dirname(path.dirname(tasksPath));
// Use mcpLog if available, otherwise use the default console log wrapper
const logger = mcpLog || {
info: (msg) => !isSilentMode() && log('info', msg),
@@ -363,7 +442,9 @@ async function expandTask(
);
if (taskIndex === -1) throw new Error(`Task ${taskId} not found`);
const task = data.tasks[taskIndex];
logger.info(`Expanding task ${taskId}: ${task.title}`);
logger.info(
`Expanding task ${taskId}: ${task.title}${useResearch ? ' with research' : ''}`
);
// --- End Task Loading/Filtering ---
// --- Handle Force Flag: Clear existing subtasks if force=true ---
@@ -381,7 +462,6 @@ async function expandTask(
let complexityReasoningContext = '';
let systemPrompt; // Declare systemPrompt here
const projectRoot = path.dirname(path.dirname(tasksPath));
const complexityReportPath = path.join(
projectRoot,
'scripts/task-complexity-report.json'
@@ -488,28 +568,27 @@ async function expandTask(
let loadingIndicator = null;
if (outputFormat === 'text') {
loadingIndicator = startLoadingIndicator(
`Generating ${finalSubtaskCount} subtasks...`
`Generating ${finalSubtaskCount} subtasks...\n`
);
}
let responseText = '';
let aiServiceResponse = null;
try {
const role = useResearch ? 'research' : 'main';
logger.info(`Using AI service with role: ${role}`);
// Call generateTextService with the determined prompts
responseText = await generateTextService({
// Call generateTextService with the determined prompts and telemetry params
aiServiceResponse = await generateTextService({
prompt: promptContent,
systemPrompt: systemPrompt, // Use the determined system prompt
systemPrompt: systemPrompt,
role,
session,
projectRoot
projectRoot,
commandName: 'expand-task',
outputType: outputFormat
});
logger.info(
'Successfully received text response from AI service',
'success'
);
responseText = aiServiceResponse.mainResult;
// Parse Subtasks
generatedSubtasks = parseSubtasksFromText(
@@ -550,14 +629,23 @@ async function expandTask(
// --- End Change: Append instead of replace ---
data.tasks[taskIndex] = task; // Assign the modified task back
logger.info(`Writing updated tasks to ${tasksPath}`);
writeJSON(tasksPath, data);
logger.info(`Generating individual task files...`);
await generateTaskFiles(tasksPath, path.dirname(tasksPath));
logger.info(`Task files generated.`);
// --- End Task Update & File Writing ---
return task; // Return the updated task object
// Display AI Usage Summary for CLI
if (
outputFormat === 'text' &&
aiServiceResponse &&
aiServiceResponse.telemetryData
) {
displayAiUsageSummary(aiServiceResponse.telemetryData, 'cli');
}
// Return the updated task object AND telemetry data
return {
task,
telemetryData: aiServiceResponse?.telemetryData
};
} catch (error) {
// Catches errors from file reading, parsing, AI call etc.
logger.error(`Error expanding task ${taskId}: ${error.message}`, 'error');

View File

@@ -1,3 +1,6 @@
import { log } from '../utils.js';
import { addComplexityToTask } from '../utils.js';
/**
* Return the next work item:
* • Prefer an eligible SUBTASK that belongs to any parent task
@@ -15,9 +18,10 @@
* ─ parentId → number (present only when it's a subtask)
*
* @param {Object[]} tasks full array of top-level tasks, each may contain .subtasks[]
* @param {Object} [complexityReport=null] - Optional complexity report object
* @returns {Object|null} next work item or null if nothing is eligible
*/
function findNextTask(tasks) {
function findNextTask(tasks, complexityReport = null) {
// ---------- helpers ----------------------------------------------------
const priorityValues = { high: 3, medium: 2, low: 1 };
@@ -91,7 +95,14 @@ function findNextTask(tasks) {
if (aPar !== bPar) return aPar - bPar;
return aSub - bSub;
});
return candidateSubtasks[0];
const nextTask = candidateSubtasks[0];
// Add complexity to the task before returning
if (nextTask && complexityReport) {
addComplexityToTask(nextTask, complexityReport);
}
return nextTask;
}
// ---------- 2) fall back to top-level tasks (original logic) ------------
@@ -116,6 +127,11 @@ function findNextTask(tasks) {
return a.id - b.id;
})[0];
// Add complexity to the task before returning
if (nextTask && complexityReport) {
addComplexityToTask(nextTask, complexityReport);
}
return nextTask;
}

View File

@@ -19,8 +19,6 @@ function generateTaskFiles(tasksPath, outputDir, options = {}) {
// Determine if we're in MCP mode by checking for mcpLog
const isMcpMode = !!options?.mcpLog;
log('info', `Preparing to regenerate task files in ${tasksPath}`);
const data = readJSON(tasksPath);
if (!data || !data.tasks) {
throw new Error(`No valid tasks found in ${tasksPath}`);
@@ -31,7 +29,7 @@ function generateTaskFiles(tasksPath, outputDir, options = {}) {
fs.mkdirSync(outputDir, { recursive: true });
}
log('info', `Found ${data.tasks.length} tasks to regenerate`);
log('info', `Preparing to regenerate ${data.tasks.length} task files`);
// Validate and fix dependencies before generating files
log('info', `Validating and fixing dependencies`);

View File

@@ -2,13 +2,20 @@ import chalk from 'chalk';
import boxen from 'boxen';
import Table from 'cli-table3';
import { log, readJSON, truncate } from '../utils.js';
import {
log,
readJSON,
truncate,
readComplexityReport,
addComplexityToTask
} from '../utils.js';
import findNextTask from './find-next-task.js';
import {
displayBanner,
getStatusWithColor,
formatDependenciesWithStatus,
getComplexityWithColor,
createProgressBar
} from '../ui.js';
@@ -16,6 +23,7 @@ import {
* List all tasks
* @param {string} tasksPath - Path to the tasks.json file
* @param {string} statusFilter - Filter by status
* @param {string} reportPath - Path to the complexity report
* @param {boolean} withSubtasks - Whether to show subtasks
* @param {string} outputFormat - Output format (text or json)
* @returns {Object} - Task list result for json format
@@ -23,6 +31,7 @@ import {
function listTasks(
tasksPath,
statusFilter,
reportPath = null,
withSubtasks = false,
outputFormat = 'text'
) {
@@ -37,6 +46,13 @@ function listTasks(
throw new Error(`No valid tasks found in ${tasksPath}`);
}
// Add complexity scores to tasks if report exists
const complexityReport = readComplexityReport(reportPath);
// Apply complexity scores to tasks
if (complexityReport && complexityReport.complexityAnalysis) {
data.tasks.forEach((task) => addComplexityToTask(task, complexityReport));
}
// Filter tasks by status if specified
const filteredTasks =
statusFilter && statusFilter.toLowerCase() !== 'all' // <-- Added check for 'all'
@@ -257,8 +273,8 @@ function listTasks(
);
const avgDependenciesPerTask = totalDependencies / data.tasks.length;
// Find next task to work on
const nextItem = findNextTask(data.tasks);
// Find next task to work on, passing the complexity report
const nextItem = findNextTask(data.tasks, complexityReport);
// Get terminal width - more reliable method
let terminalWidth;
@@ -301,8 +317,11 @@ function listTasks(
`${chalk.blue('•')} ${chalk.white('Avg dependencies per task:')} ${avgDependenciesPerTask.toFixed(1)}\n\n` +
chalk.cyan.bold('Next Task to Work On:') +
'\n' +
`ID: ${chalk.cyan(nextItem ? nextItem.id : 'N/A')} - ${nextItem ? chalk.white.bold(truncate(nextItem.title, 40)) : chalk.yellow('No task available')}\n` +
`Priority: ${nextItem ? chalk.white(nextItem.priority || 'medium') : ''} Dependencies: ${nextItem ? formatDependenciesWithStatus(nextItem.dependencies, data.tasks, true) : ''}`;
`ID: ${chalk.cyan(nextItem ? nextItem.id : 'N/A')} - ${nextItem ? chalk.white.bold(truncate(nextItem.title, 40)) : chalk.yellow('No task available')}
` +
`Priority: ${nextItem ? chalk.white(nextItem.priority || 'medium') : ''} Dependencies: ${nextItem ? formatDependenciesWithStatus(nextItem.dependencies, data.tasks, true, complexityReport) : ''}
` +
`Complexity: ${nextItem && nextItem.complexityScore ? getComplexityWithColor(nextItem.complexityScore) : chalk.gray('N/A')}`;
// Calculate width for side-by-side display
// Box borders, padding take approximately 4 chars on each side
@@ -412,9 +431,16 @@ function listTasks(
// Make dependencies column smaller as requested (-20%)
const depsWidthPct = 20;
const complexityWidthPct = 10;
// Calculate title/description width as remaining space (+20% from dependencies reduction)
const titleWidthPct =
100 - idWidthPct - statusWidthPct - priorityWidthPct - depsWidthPct;
100 -
idWidthPct -
statusWidthPct -
priorityWidthPct -
depsWidthPct -
complexityWidthPct;
// Allow 10 characters for borders and padding
const availableWidth = terminalWidth - 10;
@@ -424,6 +450,9 @@ function listTasks(
const statusWidth = Math.floor(availableWidth * (statusWidthPct / 100));
const priorityWidth = Math.floor(availableWidth * (priorityWidthPct / 100));
const depsWidth = Math.floor(availableWidth * (depsWidthPct / 100));
const complexityWidth = Math.floor(
availableWidth * (complexityWidthPct / 100)
);
const titleWidth = Math.floor(availableWidth * (titleWidthPct / 100));
// Create a table with correct borders and spacing
@@ -433,9 +462,17 @@ function listTasks(
chalk.cyan.bold('Title'),
chalk.cyan.bold('Status'),
chalk.cyan.bold('Priority'),
chalk.cyan.bold('Dependencies')
chalk.cyan.bold('Dependencies'),
chalk.cyan.bold('Complexity')
],
colWidths: [
idWidth,
titleWidth,
statusWidth,
priorityWidth,
depsWidth,
complexityWidth // Added complexity column width
],
colWidths: [idWidth, titleWidth, statusWidth, priorityWidth, depsWidth],
style: {
head: [], // No special styling for header
border: [], // No special styling for border
@@ -454,7 +491,8 @@ function listTasks(
depText = formatDependenciesWithStatus(
task.dependencies,
data.tasks,
true
true,
complexityReport
);
} else {
depText = chalk.gray('None');
@@ -480,7 +518,10 @@ function listTasks(
truncate(cleanTitle, titleWidth - 3),
status,
priorityColor(truncate(task.priority || 'medium', priorityWidth - 2)),
depText // No truncation for dependencies
depText,
task.complexityScore
? getComplexityWithColor(task.complexityScore)
: chalk.gray('N/A')
]);
// Add subtasks if requested
@@ -516,6 +557,8 @@ function listTasks(
// Default to regular task dependency
const depTask = data.tasks.find((t) => t.id === depId);
if (depTask) {
// Add complexity to depTask before checking status
addComplexityToTask(depTask, complexityReport);
const isDone =
depTask.status === 'done' || depTask.status === 'completed';
const isInProgress = depTask.status === 'in-progress';
@@ -541,7 +584,10 @@ function listTasks(
chalk.dim(`└─ ${truncate(subtask.title, titleWidth - 5)}`),
getStatusWithColor(subtask.status, true),
chalk.dim('-'),
subtaskDepText // No truncation for dependencies
subtaskDepText,
subtask.complexityScore
? chalk.gray(`${subtask.complexityScore}`)
: chalk.gray('N/A')
]);
});
}
@@ -597,6 +643,8 @@ function listTasks(
subtasksSection = `\n\n${chalk.white.bold('Subtasks:')}\n`;
subtasksSection += parentTaskForSubtasks.subtasks
.map((subtask) => {
// Add complexity to subtask before display
addComplexityToTask(subtask, complexityReport);
// Using a more simplified format for subtask status display
const status = subtask.status || 'pending';
const statusColors = {
@@ -625,8 +673,8 @@ function listTasks(
'\n\n' +
// Use nextItem.priority, nextItem.status, nextItem.dependencies
`${chalk.white('Priority:')} ${priorityColors[nextItem.priority || 'medium'](nextItem.priority || 'medium')} ${chalk.white('Status:')} ${getStatusWithColor(nextItem.status, true)}\n` +
`${chalk.white('Dependencies:')} ${nextItem.dependencies && nextItem.dependencies.length > 0 ? formatDependenciesWithStatus(nextItem.dependencies, data.tasks, true) : chalk.gray('None')}\n\n` +
// Use nextItem.description (Note: findNextTask doesn't return description, need to fetch original task/subtask for this)
`${chalk.white('Dependencies:')} ${nextItem.dependencies && nextItem.dependencies.length > 0 ? formatDependenciesWithStatus(nextItem.dependencies, data.tasks, true, complexityReport) : chalk.gray('None')}\n\n` +
// Use nextTask.description (Note: findNextTask doesn't return description, need to fetch original task/subtask for this)
// *** Fetching original item for description and details ***
`${chalk.white('Description:')} ${getWorkItemDescription(nextItem, data.tasks)}` +
subtasksSection + // <-- Subtasks are handled above now

View File

@@ -17,6 +17,7 @@ import {
import { generateObjectService } from '../ai-services-unified.js';
import { getDebugFlag } from '../config-manager.js';
import generateTaskFiles from './generate-task-files.js';
import { displayAiUsageSummary } from '../ui.js';
// Define the Zod schema for a SINGLE task object
const prdSingleTaskSchema = z.object({
@@ -47,8 +48,8 @@ const prdResponseSchema = z.object({
* @param {string} tasksPath - Path to the tasks.json file
* @param {number} numTasks - Number of tasks to generate
* @param {Object} options - Additional options
* @param {boolean} [options.useForce=false] - Whether to overwrite existing tasks.json.
* @param {boolean} [options.useAppend=false] - Append to existing tasks file.
* @param {boolean} [options.force=false] - Whether to overwrite existing tasks.json.
* @param {boolean} [options.append=false] - Append to existing tasks file.
* @param {Object} [options.reportProgress] - Function to report progress (optional, likely unused).
* @param {Object} [options.mcpLog] - MCP logger object (optional).
* @param {Object} [options.session] - Session object from MCP server (optional).
@@ -61,8 +62,8 @@ async function parsePRD(prdPath, tasksPath, numTasks, options = {}) {
mcpLog,
session,
projectRoot,
useForce = false,
useAppend = false
force = false,
append = false
} = options;
const isMCP = !!mcpLog;
const outputFormat = isMCP ? 'json' : 'text';
@@ -89,17 +90,16 @@ async function parsePRD(prdPath, tasksPath, numTasks, options = {}) {
}
};
report(
`Parsing PRD file: ${prdPath}, Force: ${useForce}, Append: ${useAppend}`
);
report(`Parsing PRD file: ${prdPath}, Force: ${force}, Append: ${append}`);
let existingTasks = [];
let nextId = 1;
let aiServiceResponse = null;
try {
// Handle file existence and overwrite/append logic
if (fs.existsSync(tasksPath)) {
if (useAppend) {
if (append) {
report(
`Append mode enabled. Reading existing tasks from ${tasksPath}`,
'info'
@@ -121,7 +121,7 @@ async function parsePRD(prdPath, tasksPath, numTasks, options = {}) {
);
existingTasks = []; // Reset if read fails
}
} else if (!useForce) {
} else if (!force) {
// Not appending and not forcing overwrite
const overwriteError = new Error(
`Output file ${tasksPath} already exists. Use --force to overwrite or --append.`
@@ -206,8 +206,8 @@ Guidelines:
// Call the unified AI service
report('Calling AI service to generate tasks from PRD...', 'info');
// Call generateObjectService with the CORRECT schema
const generatedData = await generateObjectService({
// Call generateObjectService with the CORRECT schema and additional telemetry params
aiServiceResponse = await generateObjectService({
role: 'main',
session: session,
projectRoot: projectRoot,
@@ -215,7 +215,8 @@ Guidelines:
objectName: 'tasks_data',
systemPrompt: systemPrompt,
prompt: userPrompt,
reportProgress
commandName: 'parse-prd',
outputType: isMCP ? 'mcp' : 'cli'
});
// Create the directory if it doesn't exist
@@ -223,12 +224,32 @@ Guidelines:
if (!fs.existsSync(tasksDir)) {
fs.mkdirSync(tasksDir, { recursive: true });
}
logFn.success('Successfully parsed PRD via AI service.'); // Assumes generateObjectService validated
logFn.success('Successfully parsed PRD via AI service.\n');
// Validate and Process Tasks
// const generatedData = aiServiceResponse?.mainResult?.object;
// Robustly get the actual AI-generated object
let generatedData = null;
if (aiServiceResponse?.mainResult) {
if (
typeof aiServiceResponse.mainResult === 'object' &&
aiServiceResponse.mainResult !== null &&
'tasks' in aiServiceResponse.mainResult
) {
// If mainResult itself is the object with a 'tasks' property
generatedData = aiServiceResponse.mainResult;
} else if (
typeof aiServiceResponse.mainResult.object === 'object' &&
aiServiceResponse.mainResult.object !== null &&
'tasks' in aiServiceResponse.mainResult.object
) {
// If mainResult.object is the object with a 'tasks' property
generatedData = aiServiceResponse.mainResult.object;
}
}
if (!generatedData || !Array.isArray(generatedData.tasks)) {
// This error *shouldn't* happen if generateObjectService enforced prdResponseSchema
// But keep it as a safeguard
logFn.error(
`Internal Error: generateObjectService returned unexpected data structure: ${JSON.stringify(generatedData)}`
);
@@ -265,36 +286,27 @@ Guidelines:
);
});
const allTasks = useAppend
const finalTasks = append
? [...existingTasks, ...processedNewTasks]
: processedNewTasks;
const outputData = { tasks: finalTasks };
const finalTaskData = { tasks: allTasks }; // Use the combined list
// Write the tasks to the file
writeJSON(tasksPath, finalTaskData);
// Write the final tasks to the file
writeJSON(tasksPath, outputData);
report(
`Successfully wrote ${allTasks.length} total tasks to ${tasksPath} (${processedNewTasks.length} new).`,
`Successfully ${append ? 'appended' : 'generated'} ${processedNewTasks.length} tasks in ${tasksPath}`,
'success'
);
report(`Tasks saved to: ${tasksPath}`, 'info');
// Generate individual task files
if (reportProgress && mcpLog) {
// Enable silent mode when being called from MCP server
enableSilentMode();
await generateTaskFiles(tasksPath, path.dirname(tasksPath));
disableSilentMode();
} else {
await generateTaskFiles(tasksPath, path.dirname(tasksPath));
}
// Generate markdown task files after writing tasks.json
await generateTaskFiles(tasksPath, path.dirname(tasksPath), { mcpLog });
// Only show success boxes for text output (CLI)
// Handle CLI output (e.g., success message)
if (outputFormat === 'text') {
console.log(
boxen(
chalk.green(
`Successfully generated ${processedNewTasks.length} new tasks. Total tasks in ${tasksPath}: ${allTasks.length}`
`Successfully generated ${processedNewTasks.length} new tasks. Total tasks in ${tasksPath}: ${finalTasks.length}`
),
{ padding: 1, borderColor: 'green', borderStyle: 'round' }
)
@@ -314,9 +326,18 @@ Guidelines:
}
)
);
if (aiServiceResponse && aiServiceResponse.telemetryData) {
displayAiUsageSummary(aiServiceResponse.telemetryData, 'cli');
}
}
return { success: true, tasks: processedNewTasks };
// Return telemetry data
return {
success: true,
tasksPath,
telemetryData: aiServiceResponse?.telemetryData
};
} catch (error) {
report(`Error parsing PRD: ${error.message}`, 'error');

View File

@@ -8,6 +8,10 @@ import { validateTaskDependencies } from '../dependency-manager.js';
import { getDebugFlag } from '../config-manager.js';
import updateSingleTaskStatus from './update-single-task-status.js';
import generateTaskFiles from './generate-task-files.js';
import {
isValidTaskStatus,
TASK_STATUS_OPTIONS
} from '../../../src/constants/task-status.js';
/**
* Set the status of a task
@@ -19,6 +23,11 @@ import generateTaskFiles from './generate-task-files.js';
*/
async function setTaskStatus(tasksPath, taskIdInput, newStatus, options = {}) {
try {
if (!isValidTaskStatus(newStatus)) {
throw new Error(
`Error: Invalid status value: ${newStatus}. Use one of: ${TASK_STATUS_OPTIONS.join(', ')}`
);
}
// Determine if we're in MCP mode by checking for mcpLog
const isMcpMode = !!options?.mcpLog;

View File

@@ -1,6 +1,7 @@
import chalk from 'chalk';
import { log } from '../utils.js';
import { isValidTaskStatus } from '../../../src/constants/task-status.js';
/**
* Update the status of a single task
@@ -17,6 +18,12 @@ async function updateSingleTaskStatus(
data,
showUi = true
) {
if (!isValidTaskStatus(newStatus)) {
throw new Error(
`Error: Invalid status value: ${newStatus}. Use one of: ${TASK_STATUS_OPTIONS.join(', ')}`
);
}
// Check if it's a subtask (e.g., "1.2")
if (taskIdInput.includes('.')) {
const [parentId, subtaskId] = taskIdInput

View File

@@ -3,12 +3,12 @@ import path from 'path';
import chalk from 'chalk';
import boxen from 'boxen';
import Table from 'cli-table3';
import { z } from 'zod';
import {
getStatusWithColor,
startLoadingIndicator,
stopLoadingIndicator
stopLoadingIndicator,
displayAiUsageSummary
} from '../ui.js';
import {
log as consoleLog,
@@ -17,10 +17,7 @@ import {
truncate,
isSilentMode
} from '../utils.js';
import {
generateObjectService,
generateTextService
} from '../ai-services-unified.js';
import { generateTextService } from '../ai-services-unified.js';
import { getDebugFlag } from '../config-manager.js';
import generateTaskFiles from './generate-task-files.js';
@@ -64,7 +61,6 @@ async function updateSubtaskById(
try {
report('info', `Updating subtask ${subtaskId} with prompt: "${prompt}"`);
// Validate subtask ID format
if (
!subtaskId ||
typeof subtaskId !== 'string' ||
@@ -75,19 +71,16 @@ async function updateSubtaskById(
);
}
// Validate prompt
if (!prompt || typeof prompt !== 'string' || prompt.trim() === '') {
throw new Error(
'Prompt cannot be empty. Please provide context for the subtask update.'
);
}
// Validate tasks file exists
if (!fs.existsSync(tasksPath)) {
throw new Error(`Tasks file not found at path: ${tasksPath}`);
}
// Read the tasks file
const data = readJSON(tasksPath);
if (!data || !data.tasks) {
throw new Error(
@@ -95,7 +88,6 @@ async function updateSubtaskById(
);
}
// Parse parent and subtask IDs
const [parentIdStr, subtaskIdStr] = subtaskId.split('.');
const parentId = parseInt(parentIdStr, 10);
const subtaskIdNum = parseInt(subtaskIdStr, 10);
@@ -111,7 +103,6 @@ async function updateSubtaskById(
);
}
// Find the parent task
const parentTask = data.tasks.find((task) => task.id === parentId);
if (!parentTask) {
throw new Error(
@@ -119,7 +110,6 @@ async function updateSubtaskById(
);
}
// Find the subtask
if (!parentTask.subtasks || !Array.isArray(parentTask.subtasks)) {
throw new Error(`Parent task ${parentId} has no subtasks.`);
}
@@ -135,20 +125,7 @@ async function updateSubtaskById(
const subtask = parentTask.subtasks[subtaskIndex];
const subtaskSchema = z.object({
id: z.number().int().positive(),
title: z.string(),
description: z.string().optional(),
status: z.string(),
dependencies: z.array(z.union([z.string(), z.number()])).optional(),
priority: z.string().optional(),
details: z.string().optional(),
testStrategy: z.string().optional()
});
// Only show UI elements for text output (CLI)
if (outputFormat === 'text') {
// Show the subtask that will be updated
const table = new Table({
head: [
chalk.cyan.bold('ID'),
@@ -157,13 +134,11 @@ async function updateSubtaskById(
],
colWidths: [10, 55, 10]
});
table.push([
subtaskId,
truncate(subtask.title, 52),
getStatusWithColor(subtask.status)
]);
console.log(
boxen(chalk.white.bold(`Updating Subtask #${subtaskId}`), {
padding: 1,
@@ -172,10 +147,7 @@ async function updateSubtaskById(
margin: { top: 1, bottom: 0 }
})
);
console.log(table.toString());
// Start the loading indicator - only for text output
loadingIndicator = startLoadingIndicator(
useResearch
? 'Updating subtask with research...'
@@ -183,15 +155,15 @@ async function updateSubtaskById(
);
}
let parsedAIResponse;
let generatedContentString = '';
let newlyAddedSnippet = '';
let aiServiceResponse = null;
try {
// --- GET PARENT & SIBLING CONTEXT ---
const parentContext = {
id: parentTask.id,
title: parentTask.title
// Avoid sending full parent description/details unless necessary
};
const prevSubtask =
subtaskIndex > 0
? {
@@ -200,7 +172,6 @@ async function updateSubtaskById(
status: parentTask.subtasks[subtaskIndex - 1].status
}
: null;
const nextSubtask =
subtaskIndex < parentTask.subtasks.length - 1
? {
@@ -214,154 +185,123 @@ async function updateSubtaskById(
Parent Task: ${JSON.stringify(parentContext)}
${prevSubtask ? `Previous Subtask: ${JSON.stringify(prevSubtask)}` : ''}
${nextSubtask ? `Next Subtask: ${JSON.stringify(nextSubtask)}` : ''}
Current Subtask Details (for context only):\n${subtask.details || '(No existing details)'}
`;
const systemPrompt = `You are an AI assistant updating a parent task's subtask. This subtask will be part of a larger parent task and will be used to direct AI agents to complete the subtask. Your goal is to GENERATE new, relevant information based on the user's request (which may be high-level, mid-level or low-level) and APPEND it to the existing subtask 'details' field, wrapped in specific XML-like tags with an ISO 8601 timestamp. Intelligently determine the level of detail to include based on the user's request. Some requests are meant simply to update the subtask with some mid-implementation details, while others are meant to update the subtask with a detailed plan or strategy.
const systemPrompt = `You are an AI assistant helping to update a subtask. You will be provided with the subtask's existing details, context about its parent and sibling tasks, and a user request string.
Context Provided:
- The current subtask object.
- Basic info about the parent task (ID, title).
- Basic info about the immediately preceding subtask (ID, title, status), if it exists.
- Basic info about the immediately succeeding subtask (ID, title, status), if it exists.
- A user request string.
Your Goal: Based *only* on the user's request and all the provided context (including existing details if relevant to the request), GENERATE the new text content that should be added to the subtask's details.
Focus *only* on generating the substance of the update.
Guidelines:
1. Analyze the user request considering the provided subtask details AND the context of the parent and sibling tasks.
2. GENERATE new, relevant text content that should be added to the 'details' field. Focus *only* on the substance of the update based on the user request and context. Do NOT add timestamps or any special formatting yourself. Avoid over-engineering the details, provide .
3. Update the 'details' field in the subtask object with the GENERATED text content. It's okay if this overwrites previous details in the object you return, as the calling code will handle the final appending.
4. Return the *entire* updated subtask object (with your generated content in the 'details' field) as a valid JSON object conforming to the provided schema. Do NOT return explanations or markdown formatting.`;
Output Requirements:
1. Return *only* the newly generated text content as a plain string. Do NOT return a JSON object or any other structured data.
2. Your string response should NOT include any of the subtask's original details, unless the user's request explicitly asks to rephrase, summarize, or directly modify existing text.
3. Do NOT include any timestamps, XML-like tags, markdown, or any other special formatting in your string response.
4. Ensure the generated text is concise yet complete for the update based on the user request. Avoid conversational fillers or explanations about what you are doing (e.g., do not start with "Okay, here's the update...").`;
const subtaskDataString = JSON.stringify(subtask, null, 2);
// Updated user prompt including context
const userPrompt = `Task Context:\n${contextString}\nCurrent Subtask:\n${subtaskDataString}\n\nUser Request: "${prompt}"\n\nPlease GENERATE new, relevant text content for the 'details' field based on the user request and the provided context. Return the entire updated subtask object as a valid JSON object matching the schema, with the newly generated text placed in the 'details' field.`;
// --- END UPDATED PROMPTS ---
// Pass the existing subtask.details in the user prompt for the AI's context.
const userPrompt = `Task Context:\n${contextString}\n\nUser Request: "${prompt}"\n\nBased on the User Request and all the Task Context (including current subtask details provided above), what is the new information or text that should be appended to this subtask's details? Return ONLY this new text as a plain string.`;
// Call Unified AI Service using generateObjectService
const role = useResearch ? 'research' : 'main';
report('info', `Using AI object service with role: ${role}`);
report('info', `Using AI text service with role: ${role}`);
parsedAIResponse = await generateObjectService({
aiServiceResponse = await generateTextService({
prompt: userPrompt,
systemPrompt: systemPrompt,
schema: subtaskSchema,
objectName: 'updatedSubtask',
role,
session,
projectRoot,
maxRetries: 2
maxRetries: 2,
commandName: 'update-subtask',
outputType: isMCP ? 'mcp' : 'cli'
});
report(
'success',
'Successfully received object response from AI service'
);
if (
aiServiceResponse &&
aiServiceResponse.mainResult &&
typeof aiServiceResponse.mainResult === 'string'
) {
generatedContentString = aiServiceResponse.mainResult;
} else {
generatedContentString = '';
report(
'warn',
'AI service response did not contain expected text string.'
);
}
if (outputFormat === 'text' && loadingIndicator) {
stopLoadingIndicator(loadingIndicator);
loadingIndicator = null;
}
if (!parsedAIResponse || typeof parsedAIResponse !== 'object') {
throw new Error('AI did not return a valid object.');
}
report(
'success',
`Successfully generated object using AI role: ${role}.`
);
} catch (aiError) {
report('error', `AI service call failed: ${aiError.message}`);
if (outputFormat === 'text' && loadingIndicator) {
stopLoadingIndicator(loadingIndicator); // Ensure stop on error
stopLoadingIndicator(loadingIndicator);
loadingIndicator = null;
}
throw aiError;
}
// --- TIMESTAMP & FORMATTING LOGIC (Handled Locally) ---
// Extract only the generated content from the AI's response details field.
const generatedContent = parsedAIResponse.details || ''; // Default to empty string
if (generatedContentString && generatedContentString.trim()) {
// Check if the string is not empty
const timestamp = new Date().toISOString();
const formattedBlock = `<info added on ${timestamp}>\n${generatedContentString.trim()}\n</info added on ${timestamp}>`;
newlyAddedSnippet = formattedBlock; // <--- ADD THIS LINE: Store for display
if (generatedContent.trim()) {
// Generate timestamp locally
const timestamp = new Date().toISOString(); // <<< Local Timestamp
// Format the content with XML-like tags and timestamp LOCALLY
const formattedBlock = `<info added on ${timestamp}>\n${generatedContent.trim()}\n</info added on ${timestamp}>`; // <<< Local Formatting
// Append the formatted block to the *original* subtask details
subtask.details =
(subtask.details ? subtask.details + '\n' : '') + formattedBlock; // <<< Local Appending
report(
'info',
'Appended timestamped, formatted block with AI-generated content to subtask.details.'
);
(subtask.details ? subtask.details + '\n' : '') + formattedBlock;
} else {
report(
'warn',
'AI response object did not contain generated content in the "details" field. Original details remain unchanged.'
'AI response was empty or whitespace after trimming. Original details remain unchanged.'
);
newlyAddedSnippet = 'No new details were added by the AI.';
}
// --- END TIMESTAMP & FORMATTING LOGIC ---
// Get a reference to the subtask *after* its details have been updated
const updatedSubtask = parentTask.subtasks[subtaskIndex]; // subtask === updatedSubtask now
const updatedSubtask = parentTask.subtasks[subtaskIndex];
report('info', 'Updated subtask details locally after AI generation.');
// --- END UPDATE SUBTASK ---
// Only show debug info for text output (CLI)
if (outputFormat === 'text' && getDebugFlag(session)) {
console.log(
'>>> DEBUG: Subtask details AFTER AI update:',
updatedSubtask.details // Use updatedSubtask
updatedSubtask.details
);
}
// Description update logic (keeping as is for now)
if (updatedSubtask.description) {
// Use updatedSubtask
if (prompt.length < 100) {
if (outputFormat === 'text' && getDebugFlag(session)) {
console.log(
'>>> DEBUG: Subtask description BEFORE append:',
updatedSubtask.description // Use updatedSubtask
updatedSubtask.description
);
}
updatedSubtask.description += ` [Updated: ${new Date().toLocaleDateString()}]`; // Use updatedSubtask
updatedSubtask.description += ` [Updated: ${new Date().toLocaleDateString()}]`;
if (outputFormat === 'text' && getDebugFlag(session)) {
console.log(
'>>> DEBUG: Subtask description AFTER append:',
updatedSubtask.description // Use updatedSubtask
updatedSubtask.description
);
}
}
}
// Only show debug info for text output (CLI)
if (outputFormat === 'text' && getDebugFlag(session)) {
console.log('>>> DEBUG: About to call writeJSON with updated data...');
}
// Write the updated tasks to the file (parentTask already contains the updated subtask)
writeJSON(tasksPath, data);
// Only show debug info for text output (CLI)
if (outputFormat === 'text' && getDebugFlag(session)) {
console.log('>>> DEBUG: writeJSON call completed.');
}
report('success', `Successfully updated subtask ${subtaskId}`);
// Generate individual task files
await generateTaskFiles(tasksPath, path.dirname(tasksPath));
// Stop indicator before final console output - only for text output (CLI)
if (outputFormat === 'text') {
if (loadingIndicator) {
stopLoadingIndicator(loadingIndicator);
loadingIndicator = null;
}
console.log(
boxen(
chalk.green(`Successfully updated subtask #${subtaskId}`) +
@@ -370,31 +310,30 @@ Guidelines:
' ' +
updatedSubtask.title +
'\n\n' +
// Update the display to show the new details field
chalk.white.bold('Updated Details:') +
chalk.white.bold('Newly Added Snippet:') +
'\n' +
chalk.white(truncate(updatedSubtask.details || '', 500, true)), // Use updatedSubtask
chalk.white(newlyAddedSnippet),
{ padding: 1, borderColor: 'green', borderStyle: 'round' }
)
);
}
return updatedSubtask; // Return the modified subtask object
if (outputFormat === 'text' && aiServiceResponse.telemetryData) {
displayAiUsageSummary(aiServiceResponse.telemetryData, 'cli');
}
return {
updatedSubtask: updatedSubtask,
telemetryData: aiServiceResponse.telemetryData
};
} catch (error) {
// Outer catch block handles final errors after loop/attempts
// Stop indicator on error - only for text output (CLI)
if (outputFormat === 'text' && loadingIndicator) {
stopLoadingIndicator(loadingIndicator);
loadingIndicator = null;
}
report('error', `Error updating subtask: ${error.message}`);
// Only show error UI for text output (CLI)
if (outputFormat === 'text') {
console.error(chalk.red(`Error: ${error.message}`));
// Provide helpful error messages based on error type
if (error.message?.includes('ANTHROPIC_API_KEY')) {
console.log(
chalk.yellow('\nTo fix this issue, set your Anthropic API key:')
@@ -409,7 +348,6 @@ Guidelines:
' 2. Or run without the research flag: task-master update-subtask --id=<id> --prompt="..."'
);
} else if (error.message?.includes('overloaded')) {
// Catch final overload error
console.log(
chalk.yellow(
'\nAI model overloaded, and fallback failed or was unavailable:'
@@ -417,7 +355,6 @@ Guidelines:
);
console.log(' 1. Try again in a few minutes.');
console.log(' 2. Ensure PERPLEXITY_API_KEY is set for fallback.');
console.log(' 3. Consider breaking your prompt into smaller updates.');
} else if (error.message?.includes('not found')) {
console.log(chalk.yellow('\nTo fix this issue:'));
console.log(
@@ -426,22 +363,22 @@ Guidelines:
console.log(
' 2. Use a valid subtask ID with the --id parameter in format "parentId.subtaskId"'
);
} else if (error.message?.includes('empty stream response')) {
} else if (
error.message?.includes('empty stream response') ||
error.message?.includes('AI did not return a valid text string')
) {
console.log(
chalk.yellow(
'\nThe AI model returned an empty response. This might be due to the prompt or API issues. Try rephrasing or trying again later.'
'\nThe AI model returned an empty or invalid response. This might be due to the prompt or API issues. Try rephrasing or trying again later.'
)
);
}
if (getDebugFlag(session)) {
// Use getter
console.error(error);
}
} else {
throw error; // Re-throw for JSON output
throw error;
}
return null;
}
}

View File

@@ -16,7 +16,8 @@ import {
import {
getStatusWithColor,
startLoadingIndicator,
stopLoadingIndicator
stopLoadingIndicator,
displayAiUsageSummary
} from '../ui.js';
import { generateTextService } from '../ai-services-unified.js';
@@ -94,10 +95,6 @@ function parseUpdatedTaskFromText(text, expectedTaskId, logFn, isMCP) {
// It worked! Use this as the primary cleaned response.
cleanedResponse = potentialJsonFromBraces;
parseMethodUsed = 'braces';
report(
'info',
'Successfully parsed JSON content extracted between first { and last }.'
);
} catch (e) {
report(
'info',
@@ -376,29 +373,125 @@ The changes described in the prompt should be thoughtfully applied to make the t
const userPrompt = `Here is the task to update:\n${taskDataString}\n\nPlease update this task based on the following new context:\n${prompt}\n\nIMPORTANT: In the task JSON above, any subtasks with "status": "done" or "status": "completed" should be preserved exactly as is. Build your changes around these completed items.\n\nReturn only the updated task as a valid JSON object.`;
// --- End Build Prompts ---
let updatedTask;
let loadingIndicator = null;
if (outputFormat === 'text') {
let aiServiceResponse = null;
if (!isMCP && outputFormat === 'text') {
loadingIndicator = startLoadingIndicator(
useResearch ? 'Updating task with research...\n' : 'Updating task...\n'
);
}
let responseText = '';
try {
// --- Call Unified AI Service (generateTextService) ---
const role = useResearch ? 'research' : 'main';
report('info', `Using AI service with role: ${role}`);
responseText = await generateTextService({
prompt: userPrompt,
const serviceRole = useResearch ? 'research' : 'main';
aiServiceResponse = await generateTextService({
role: serviceRole,
session: session,
projectRoot: projectRoot,
systemPrompt: systemPrompt,
role,
session,
projectRoot
prompt: userPrompt,
commandName: 'update-task',
outputType: isMCP ? 'mcp' : 'cli'
});
report('success', 'Successfully received text response from AI service');
// --- End AI Service Call ---
if (loadingIndicator)
stopLoadingIndicator(loadingIndicator, 'AI update complete.');
// Use mainResult (text) for parsing
const updatedTask = parseUpdatedTaskFromText(
aiServiceResponse.mainResult,
taskId,
logFn,
isMCP
);
// --- Task Validation/Correction (Keep existing logic) ---
if (!updatedTask || typeof updatedTask !== 'object')
throw new Error('Received invalid task object from AI.');
if (!updatedTask.title || !updatedTask.description)
throw new Error('Updated task missing required fields.');
// Preserve ID if AI changed it
if (updatedTask.id !== taskId) {
report('warn', `AI changed task ID. Restoring original ID ${taskId}.`);
updatedTask.id = taskId;
}
// Preserve status if AI changed it
if (
updatedTask.status !== taskToUpdate.status &&
!prompt.toLowerCase().includes('status')
) {
report(
'warn',
`AI changed task status. Restoring original status '${taskToUpdate.status}'.`
);
updatedTask.status = taskToUpdate.status;
}
// Preserve completed subtasks (Keep existing logic)
if (taskToUpdate.subtasks?.length > 0) {
if (!updatedTask.subtasks) {
report(
'warn',
'Subtasks removed by AI. Restoring original subtasks.'
);
updatedTask.subtasks = taskToUpdate.subtasks;
} else {
const completedOriginal = taskToUpdate.subtasks.filter(
(st) => st.status === 'done' || st.status === 'completed'
);
completedOriginal.forEach((compSub) => {
const updatedSub = updatedTask.subtasks.find(
(st) => st.id === compSub.id
);
if (
!updatedSub ||
JSON.stringify(updatedSub) !== JSON.stringify(compSub)
) {
report(
'warn',
`Completed subtask ${compSub.id} was modified or removed. Restoring.`
);
// Remove potentially modified version
updatedTask.subtasks = updatedTask.subtasks.filter(
(st) => st.id !== compSub.id
);
// Add back original
updatedTask.subtasks.push(compSub);
}
});
// Deduplicate just in case
const subtaskIds = new Set();
updatedTask.subtasks = updatedTask.subtasks.filter((st) => {
if (!subtaskIds.has(st.id)) {
subtaskIds.add(st.id);
return true;
}
report('warn', `Duplicate subtask ID ${st.id} removed.`);
return false;
});
}
}
// --- End Task Validation/Correction ---
// --- Update Task Data (Keep existing) ---
data.tasks[taskIndex] = updatedTask;
// --- End Update Task Data ---
// --- Write File and Generate (Unchanged) ---
writeJSON(tasksPath, data);
report('success', `Successfully updated task ${taskId}`);
await generateTaskFiles(tasksPath, path.dirname(tasksPath));
// --- End Write File ---
// --- Display CLI Telemetry ---
if (outputFormat === 'text' && aiServiceResponse.telemetryData) {
displayAiUsageSummary(aiServiceResponse.telemetryData, 'cli'); // <<< ADD display
}
// --- Return Success with Telemetry ---
return {
updatedTask: updatedTask, // Return the updated task object
telemetryData: aiServiceResponse.telemetryData // <<< ADD telemetryData
};
} catch (error) {
// Catch errors from generateTextService
if (loadingIndicator) stopLoadingIndicator(loadingIndicator);
@@ -407,114 +500,7 @@ The changes described in the prompt should be thoughtfully applied to make the t
report('error', 'Please ensure API keys are configured correctly.');
}
throw error; // Re-throw error
} finally {
if (loadingIndicator) stopLoadingIndicator(loadingIndicator);
}
// --- Parse and Validate Response ---
try {
// Pass logFn and isMCP flag to the parser
updatedTask = parseUpdatedTaskFromText(
responseText,
taskId,
logFn,
isMCP
);
} catch (parseError) {
report(
'error',
`Failed to parse updated task from AI response: ${parseError.message}`
);
if (getDebugFlag(session)) {
report('error', `Raw AI Response:\n${responseText}`);
}
throw new Error(
`Failed to parse valid updated task from AI response: ${parseError.message}`
);
}
// --- End Parse/Validate ---
// --- Task Validation/Correction (Keep existing logic) ---
if (!updatedTask || typeof updatedTask !== 'object')
throw new Error('Received invalid task object from AI.');
if (!updatedTask.title || !updatedTask.description)
throw new Error('Updated task missing required fields.');
// Preserve ID if AI changed it
if (updatedTask.id !== taskId) {
report('warn', `AI changed task ID. Restoring original ID ${taskId}.`);
updatedTask.id = taskId;
}
// Preserve status if AI changed it
if (
updatedTask.status !== taskToUpdate.status &&
!prompt.toLowerCase().includes('status')
) {
report(
'warn',
`AI changed task status. Restoring original status '${taskToUpdate.status}'.`
);
updatedTask.status = taskToUpdate.status;
}
// Preserve completed subtasks (Keep existing logic)
if (taskToUpdate.subtasks?.length > 0) {
if (!updatedTask.subtasks) {
report('warn', 'Subtasks removed by AI. Restoring original subtasks.');
updatedTask.subtasks = taskToUpdate.subtasks;
} else {
const completedOriginal = taskToUpdate.subtasks.filter(
(st) => st.status === 'done' || st.status === 'completed'
);
completedOriginal.forEach((compSub) => {
const updatedSub = updatedTask.subtasks.find(
(st) => st.id === compSub.id
);
if (
!updatedSub ||
JSON.stringify(updatedSub) !== JSON.stringify(compSub)
) {
report(
'warn',
`Completed subtask ${compSub.id} was modified or removed. Restoring.`
);
// Remove potentially modified version
updatedTask.subtasks = updatedTask.subtasks.filter(
(st) => st.id !== compSub.id
);
// Add back original
updatedTask.subtasks.push(compSub);
}
});
// Deduplicate just in case
const subtaskIds = new Set();
updatedTask.subtasks = updatedTask.subtasks.filter((st) => {
if (!subtaskIds.has(st.id)) {
subtaskIds.add(st.id);
return true;
}
report('warn', `Duplicate subtask ID ${st.id} removed.`);
return false;
});
}
}
// --- End Task Validation/Correction ---
// --- Update Task Data (Keep existing) ---
data.tasks[taskIndex] = updatedTask;
// --- End Update Task Data ---
// --- Write File and Generate (Keep existing) ---
writeJSON(tasksPath, data);
report('success', `Successfully updated task ${taskId}`);
await generateTaskFiles(tasksPath, path.dirname(tasksPath));
// --- End Write File ---
// --- Final CLI Output (Keep existing) ---
if (outputFormat === 'text') {
/* ... success boxen ... */
}
// --- End Final CLI Output ---
return updatedTask; // Return the updated task
} catch (error) {
// General error catch
// --- General Error Handling (Keep existing) ---

View File

@@ -15,7 +15,8 @@ import {
import {
getStatusWithColor,
startLoadingIndicator,
stopLoadingIndicator
stopLoadingIndicator,
displayAiUsageSummary
} from '../ui.js';
import { getDebugFlag } from '../config-manager.js';
@@ -93,10 +94,6 @@ function parseUpdatedTasksFromText(text, expectedCount, logFn, isMCP) {
// It worked! Use this as the primary cleaned response.
cleanedResponse = potentialJsonFromArray;
parseMethodUsed = 'brackets';
report(
'info',
'Successfully parsed JSON content extracted between first [ and last ].'
);
} catch (e) {
report(
'info',
@@ -350,31 +347,100 @@ The changes described in the prompt should be applied to ALL tasks in the list.`
const userPrompt = `Here are the tasks to update:\n${taskDataString}\n\nPlease update these tasks based on the following new context:\n${prompt}\n\nIMPORTANT: In the tasks JSON above, any subtasks with "status": "done" or "status": "completed" should be preserved exactly as is. Build your changes around these completed items.\n\nReturn only the updated tasks as a valid JSON array.`;
// --- End Build Prompts ---
// --- AI Call ---
let loadingIndicator = null;
if (outputFormat === 'text') {
loadingIndicator = startLoadingIndicator('Updating tasks...\n');
let aiServiceResponse = null;
if (!isMCP && outputFormat === 'text') {
loadingIndicator = startLoadingIndicator('Updating tasks with AI...\n');
}
let responseText = '';
let updatedTasks;
try {
// --- Call Unified AI Service ---
const role = useResearch ? 'research' : 'main';
if (isMCP) logFn.info(`Using AI service with role: ${role}`);
else logFn('info', `Using AI service with role: ${role}`);
// Determine role based on research flag
const serviceRole = useResearch ? 'research' : 'main';
responseText = await generateTextService({
prompt: userPrompt,
// Call the unified AI service
aiServiceResponse = await generateTextService({
role: serviceRole,
session: session,
projectRoot: projectRoot,
systemPrompt: systemPrompt,
role,
session,
projectRoot
prompt: userPrompt,
commandName: 'update-tasks',
outputType: isMCP ? 'mcp' : 'cli'
});
if (isMCP) logFn.info('Successfully received text response');
if (loadingIndicator)
stopLoadingIndicator(loadingIndicator, 'AI update complete.');
// Use the mainResult (text) for parsing
const parsedUpdatedTasks = parseUpdatedTasksFromText(
aiServiceResponse.mainResult,
tasksToUpdate.length,
logFn,
isMCP
);
// --- Update Tasks Data (Unchanged) ---
if (!Array.isArray(parsedUpdatedTasks)) {
// Should be caught by parser, but extra check
throw new Error(
'Parsed AI response for updated tasks was not an array.'
);
}
if (isMCP)
logFn.info(
`Received ${parsedUpdatedTasks.length} updated tasks from AI.`
);
else
logFn('success', 'Successfully received text response via AI service');
// --- End AI Service Call ---
logFn(
'info',
`Received ${parsedUpdatedTasks.length} updated tasks from AI.`
);
// Create a map for efficient lookup
const updatedTasksMap = new Map(
parsedUpdatedTasks.map((task) => [task.id, task])
);
let actualUpdateCount = 0;
data.tasks.forEach((task, index) => {
if (updatedTasksMap.has(task.id)) {
// Only update if the task was part of the set sent to AI
data.tasks[index] = updatedTasksMap.get(task.id);
actualUpdateCount++;
}
});
if (isMCP)
logFn.info(
`Applied updates to ${actualUpdateCount} tasks in the dataset.`
);
else
logFn(
'info',
`Applied updates to ${actualUpdateCount} tasks in the dataset.`
);
writeJSON(tasksPath, data);
if (isMCP)
logFn.info(
`Successfully updated ${actualUpdateCount} tasks in ${tasksPath}`
);
else
logFn(
'success',
`Successfully updated ${actualUpdateCount} tasks in ${tasksPath}`
);
await generateTaskFiles(tasksPath, path.dirname(tasksPath));
if (outputFormat === 'text' && aiServiceResponse.telemetryData) {
displayAiUsageSummary(aiServiceResponse.telemetryData, 'cli');
}
return {
success: true,
updatedTasks: parsedUpdatedTasks,
telemetryData: aiServiceResponse.telemetryData
};
} catch (error) {
if (loadingIndicator) stopLoadingIndicator(loadingIndicator);
if (isMCP) logFn.error(`Error during AI service call: ${error.message}`);
@@ -390,98 +456,10 @@ The changes described in the prompt should be applied to ALL tasks in the list.`
'Please ensure API keys are configured correctly in .env or mcp.json.'
);
}
throw error; // Re-throw error
throw error;
} finally {
if (loadingIndicator) stopLoadingIndicator(loadingIndicator);
}
// --- Parse and Validate Response ---
try {
updatedTasks = parseUpdatedTasksFromText(
responseText,
tasksToUpdate.length,
logFn,
isMCP
);
} catch (parseError) {
if (isMCP)
logFn.error(
`Failed to parse updated tasks from AI response: ${parseError.message}`
);
else
logFn(
'error',
`Failed to parse updated tasks from AI response: ${parseError.message}`
);
if (getDebugFlag(session)) {
if (isMCP) logFn.error(`Raw AI Response:\n${responseText}`);
else logFn('error', `Raw AI Response:\n${responseText}`);
}
throw new Error(
`Failed to parse valid updated tasks from AI response: ${parseError.message}`
);
}
// --- End Parse/Validate ---
// --- Update Tasks Data (Unchanged) ---
if (!Array.isArray(updatedTasks)) {
// Should be caught by parser, but extra check
throw new Error('Parsed AI response for updated tasks was not an array.');
}
if (isMCP)
logFn.info(`Received ${updatedTasks.length} updated tasks from AI.`);
else
logFn('info', `Received ${updatedTasks.length} updated tasks from AI.`);
// Create a map for efficient lookup
const updatedTasksMap = new Map(
updatedTasks.map((task) => [task.id, task])
);
// Iterate through the original data and update based on the map
let actualUpdateCount = 0;
data.tasks.forEach((task, index) => {
if (updatedTasksMap.has(task.id)) {
// Only update if the task was part of the set sent to AI
data.tasks[index] = updatedTasksMap.get(task.id);
actualUpdateCount++;
}
});
if (isMCP)
logFn.info(
`Applied updates to ${actualUpdateCount} tasks in the dataset.`
);
else
logFn(
'info',
`Applied updates to ${actualUpdateCount} tasks in the dataset.`
);
// --- End Update Tasks Data ---
// --- Write File and Generate (Unchanged) ---
writeJSON(tasksPath, data);
if (isMCP)
logFn.info(
`Successfully updated ${actualUpdateCount} tasks in ${tasksPath}`
);
else
logFn(
'success',
`Successfully updated ${actualUpdateCount} tasks in ${tasksPath}`
);
await generateTaskFiles(tasksPath, path.dirname(tasksPath));
// --- End Write File ---
// --- Final CLI Output (Unchanged) ---
if (outputFormat === 'text') {
console.log(
boxen(chalk.green(`Successfully updated ${actualUpdateCount} tasks`), {
padding: 1,
borderColor: 'green',
borderStyle: 'round'
})
);
}
// --- End Final CLI Output ---
} catch (error) {
// --- General Error Handling (Unchanged) ---
if (isMCP) logFn.error(`Error updating tasks: ${error.message}`);

View File

@@ -16,10 +16,15 @@ import {
truncate,
isSilentMode
} from './utils.js';
import path from 'path';
import fs from 'fs';
import { findNextTask, analyzeTaskComplexity } from './task-manager.js';
import {
findNextTask,
analyzeTaskComplexity,
readComplexityReport
} from './task-manager.js';
import { getProjectName, getDefaultSubtasks } from './config-manager.js';
import { TASK_STATUS_OPTIONS } from '../../src/constants/task-status.js';
import { getTaskMasterVersion } from '../../src/utils/getVersion.js';
// Create a color gradient for the banner
const coolGradient = gradient(['#00b4d8', '#0077b6', '#03045e']);
@@ -46,17 +51,7 @@ function displayBanner() {
);
// Read version directly from package.json
let version = 'unknown'; // Initialize with a default
try {
const packageJsonPath = path.join(process.cwd(), 'package.json');
if (fs.existsSync(packageJsonPath)) {
const packageJson = JSON.parse(fs.readFileSync(packageJsonPath, 'utf8'));
version = packageJson.version;
}
} catch (error) {
// Silently fall back to default version
log('warn', 'Could not read package.json for version info.');
}
const version = getTaskMasterVersion();
console.log(
boxen(
@@ -273,12 +268,14 @@ function getStatusWithColor(status, forTable = false) {
* @param {Array} dependencies - Array of dependency IDs
* @param {Array} allTasks - Array of all tasks
* @param {boolean} forConsole - Whether the output is for console display
* @param {Object|null} complexityReport - Optional pre-loaded complexity report
* @returns {string} Formatted dependencies string
*/
function formatDependenciesWithStatus(
dependencies,
allTasks,
forConsole = false
forConsole = false,
complexityReport = null // Add complexityReport parameter
) {
if (
!dependencies ||
@@ -342,7 +339,11 @@ function formatDependenciesWithStatus(
typeof depId === 'string' ? parseInt(depId, 10) : depId;
// Look up the task using the numeric ID
const depTaskResult = findTaskById(allTasks, numericDepId);
const depTaskResult = findTaskById(
allTasks,
numericDepId,
complexityReport
);
const depTask = depTaskResult.task; // Access the task object from the result
if (!depTask) {
@@ -458,7 +459,7 @@ function displayHelp() {
{
name: 'set-status',
args: '--id=<id> --status=<status>',
desc: 'Update task status (done, pending, etc.)'
desc: `Update task status (${TASK_STATUS_OPTIONS.join(', ')})`
},
{
name: 'update',
@@ -761,7 +762,7 @@ function truncateString(str, maxLength) {
* Display the next task to work on
* @param {string} tasksPath - Path to the tasks.json file
*/
async function displayNextTask(tasksPath) {
async function displayNextTask(tasksPath, complexityReportPath = null) {
displayBanner();
// Read the tasks file
@@ -771,8 +772,11 @@ async function displayNextTask(tasksPath) {
process.exit(1);
}
// Read complexity report once
const complexityReport = readComplexityReport(complexityReportPath);
// Find the next task
const nextTask = findNextTask(data.tasks);
const nextTask = findNextTask(data.tasks, complexityReport);
if (!nextTask) {
console.log(
@@ -809,12 +813,7 @@ async function displayNextTask(tasksPath) {
'padding-bottom': 0,
compact: true
},
chars: {
mid: '',
'left-mid': '',
'mid-mid': '',
'right-mid': ''
},
chars: { mid: '', 'left-mid': '', 'mid-mid': '', 'right-mid': '' },
colWidths: [15, Math.min(75, process.stdout.columns - 20 || 60)],
wordWrap: true
});
@@ -838,7 +837,18 @@ async function displayNextTask(tasksPath) {
],
[
chalk.cyan.bold('Dependencies:'),
formatDependenciesWithStatus(nextTask.dependencies, data.tasks, true)
formatDependenciesWithStatus(
nextTask.dependencies,
data.tasks,
true,
complexityReport
)
],
[
chalk.cyan.bold('Complexity:'),
nextTask.complexityScore
? getComplexityWithColor(nextTask.complexityScore)
: chalk.gray('N/A')
],
[chalk.cyan.bold('Description:'), nextTask.description]
);
@@ -860,8 +870,11 @@ async function displayNextTask(tasksPath) {
);
}
// Show subtasks if they exist
if (nextTask.subtasks && nextTask.subtasks.length > 0) {
// Determine if the nextTask is a subtask
const isSubtask = !!nextTask.parentId;
// Show subtasks if they exist (only for parent tasks)
if (!isSubtask && nextTask.subtasks && nextTask.subtasks.length > 0) {
console.log(
boxen(chalk.white.bold('Subtasks'), {
padding: { top: 0, bottom: 0, left: 1, right: 1 },
@@ -902,12 +915,7 @@ async function displayNextTask(tasksPath) {
'padding-bottom': 0,
compact: true
},
chars: {
mid: '',
'left-mid': '',
'mid-mid': '',
'right-mid': ''
},
chars: { mid: '', 'left-mid': '', 'mid-mid': '', 'right-mid': '' },
wordWrap: true
});
@@ -966,8 +974,10 @@ async function displayNextTask(tasksPath) {
});
console.log(subtaskTable.toString());
} else {
// Suggest expanding if no subtasks
}
// Suggest expanding if no subtasks (only for parent tasks without subtasks)
if (!isSubtask && (!nextTask.subtasks || nextTask.subtasks.length === 0)) {
console.log(
boxen(
chalk.yellow('No subtasks found. Consider breaking down this task:') +
@@ -986,22 +996,30 @@ async function displayNextTask(tasksPath) {
}
// Show action suggestions
let suggestedActionsContent = chalk.white.bold('Suggested Actions:') + '\n';
if (isSubtask) {
// Suggested actions for a subtask
suggestedActionsContent +=
`${chalk.cyan('1.')} Mark as in-progress: ${chalk.yellow(`task-master set-status --id=${nextTask.id} --status=in-progress`)}\n` +
`${chalk.cyan('2.')} Mark as done when completed: ${chalk.yellow(`task-master set-status --id=${nextTask.id} --status=done`)}\n` +
`${chalk.cyan('3.')} View parent task: ${chalk.yellow(`task-master show --id=${nextTask.parentId}`)}`;
} else {
// Suggested actions for a parent task
suggestedActionsContent +=
`${chalk.cyan('1.')} Mark as in-progress: ${chalk.yellow(`task-master set-status --id=${nextTask.id} --status=in-progress`)}\n` +
`${chalk.cyan('2.')} Mark as done when completed: ${chalk.yellow(`task-master set-status --id=${nextTask.id} --status=done`)}\n` +
(nextTask.subtasks && nextTask.subtasks.length > 0
? `${chalk.cyan('3.')} Update subtask status: ${chalk.yellow(`task-master set-status --id=${nextTask.id}.1 --status=done`)}` // Example: first subtask
: `${chalk.cyan('3.')} Break down into subtasks: ${chalk.yellow(`task-master expand --id=${nextTask.id}`)}`);
}
console.log(
boxen(
chalk.white.bold('Suggested Actions:') +
'\n' +
`${chalk.cyan('1.')} Mark as in-progress: ${chalk.yellow(`task-master set-status --id=${nextTask.id} --status=in-progress`)}\n` +
`${chalk.cyan('2.')} Mark as done when completed: ${chalk.yellow(`task-master set-status --id=${nextTask.id} --status=done`)}\n` +
(nextTask.subtasks && nextTask.subtasks.length > 0
? `${chalk.cyan('3.')} Update subtask status: ${chalk.yellow(`task-master set-status --id=${nextTask.id}.1 --status=done`)}`
: `${chalk.cyan('3.')} Break down into subtasks: ${chalk.yellow(`task-master expand --id=${nextTask.id}`)}`),
{
padding: { top: 0, bottom: 0, left: 1, right: 1 },
borderColor: 'green',
borderStyle: 'round',
margin: { top: 1 }
}
)
boxen(suggestedActionsContent, {
padding: { top: 0, bottom: 0, left: 1, right: 1 },
borderColor: 'green',
borderStyle: 'round',
margin: { top: 1 }
})
);
}
@@ -1011,7 +1029,12 @@ async function displayNextTask(tasksPath) {
* @param {string|number} taskId - The ID of the task to display
* @param {string} [statusFilter] - Optional status to filter subtasks by
*/
async function displayTaskById(tasksPath, taskId, statusFilter = null) {
async function displayTaskById(
tasksPath,
taskId,
complexityReportPath = null,
statusFilter = null
) {
displayBanner();
// Read the tasks file
@@ -1021,11 +1044,15 @@ async function displayTaskById(tasksPath, taskId, statusFilter = null) {
process.exit(1);
}
// Read complexity report once
const complexityReport = readComplexityReport(complexityReportPath);
// Find the task by ID, applying the status filter if provided
// Returns { task, originalSubtaskCount, originalSubtasks }
const { task, originalSubtaskCount, originalSubtasks } = findTaskById(
data.tasks,
taskId,
complexityReport,
statusFilter
);
@@ -1080,6 +1107,12 @@ async function displayTaskById(tasksPath, taskId, statusFilter = null) {
chalk.cyan.bold('Status:'),
getStatusWithColor(task.status || 'pending', true)
],
[
chalk.cyan.bold('Complexity:'),
task.complexityScore
? getComplexityWithColor(task.complexityScore)
: chalk.gray('N/A')
],
[
chalk.cyan.bold('Description:'),
task.description || 'No description provided.'
@@ -1158,7 +1191,18 @@ async function displayTaskById(tasksPath, taskId, statusFilter = null) {
[chalk.cyan.bold('Priority:'), priorityColor(task.priority || 'medium')],
[
chalk.cyan.bold('Dependencies:'),
formatDependenciesWithStatus(task.dependencies, data.tasks, true)
formatDependenciesWithStatus(
task.dependencies,
data.tasks,
true,
complexityReport
)
],
[
chalk.cyan.bold('Complexity:'),
task.complexityScore
? getComplexityWithColor(task.complexityScore)
: chalk.gray('N/A')
],
[chalk.cyan.bold('Description:'), task.description]
);
@@ -2004,6 +2048,51 @@ function displayAvailableModels(availableModels) {
);
}
/**
* Displays AI usage telemetry summary in the CLI.
* @param {object} telemetryData - The telemetry data object.
* @param {string} outputType - 'cli' or 'mcp' (though typically only called for 'cli').
*/
function displayAiUsageSummary(telemetryData, outputType = 'cli') {
if (
(outputType !== 'cli' && outputType !== 'text') ||
!telemetryData ||
isSilentMode()
) {
return; // Only display for CLI and if data exists and not in silent mode
}
const {
modelUsed,
providerName,
inputTokens,
outputTokens,
totalTokens,
totalCost,
commandName
} = telemetryData;
let summary = chalk.bold.blue('AI Usage Summary:') + '\n';
summary += chalk.gray(` Command: ${commandName}\n`);
summary += chalk.gray(` Provider: ${providerName}\n`);
summary += chalk.gray(` Model: ${modelUsed}\n`);
summary += chalk.gray(
` Tokens: ${totalTokens} (Input: ${inputTokens}, Output: ${outputTokens})\n`
);
summary += chalk.gray(` Est. Cost: $${totalCost.toFixed(6)}`);
console.log(
boxen(summary, {
padding: 1,
margin: { top: 1 },
borderColor: 'blue',
borderStyle: 'round',
title: '💡 Telemetry',
titleAlignment: 'center'
})
);
}
// Export UI functions
export {
displayBanner,
@@ -2022,5 +2111,6 @@ export {
displayApiKeyStatus,
displayModelConfiguration,
displayAvailableModels,
displayAiUsageSummary,
confirmRulesRemove
};

View File

@@ -275,6 +275,22 @@ function findTaskInComplexityReport(report, taskId) {
return report.complexityAnalysis.find((task) => task.taskId === taskId);
}
function addComplexityToTask(task, complexityReport) {
let taskId;
if (task.isSubtask) {
taskId = task.parentTask.id;
} else if (task.parentId) {
taskId = task.parentId;
} else {
taskId = task.id;
}
const taskAnalysis = findTaskInComplexityReport(complexityReport, taskId);
if (taskAnalysis) {
task.complexityScore = taskAnalysis.complexityScore;
}
}
/**
* Checks if a task exists in the tasks array
* @param {Array} tasks - The tasks array
@@ -325,10 +341,17 @@ function formatTaskId(id) {
* Finds a task by ID in the tasks array. Optionally filters subtasks by status.
* @param {Array} tasks - The tasks array
* @param {string|number} taskId - The task ID to find
* @param {Object|null} complexityReport - Optional pre-loaded complexity report
* @returns {Object|null} The task object or null if not found
* @param {string} [statusFilter] - Optional status to filter subtasks by
* @returns {{task: Object|null, originalSubtaskCount: number|null}} The task object (potentially with filtered subtasks) and the original subtask count if filtered, or nulls if not found.
*/
function findTaskById(tasks, taskId, statusFilter = null) {
function findTaskById(
tasks,
taskId,
complexityReport = null,
statusFilter = null
) {
if (!taskId || !tasks || !Array.isArray(tasks)) {
return { task: null, originalSubtaskCount: null };
}
@@ -356,10 +379,17 @@ function findTaskById(tasks, taskId, statusFilter = null) {
subtask.isSubtask = true;
}
// Return the found subtask (or null) and null for originalSubtaskCount
// If we found a task, check for complexity data
if (subtask && complexityReport) {
addComplexityToTask(subtask, complexityReport);
}
return { task: subtask || null, originalSubtaskCount: null };
}
let taskResult = null;
let originalSubtaskCount = null;
// Find the main task
const id = parseInt(taskId, 10);
const task = tasks.find((t) => t.id === id) || null;
@@ -369,6 +399,8 @@ function findTaskById(tasks, taskId, statusFilter = null) {
return { task: null, originalSubtaskCount: null };
}
taskResult = task;
// If task found and statusFilter provided, filter its subtasks
if (statusFilter && task.subtasks && Array.isArray(task.subtasks)) {
const originalSubtaskCount = task.subtasks.length;
@@ -379,12 +411,18 @@ function findTaskById(tasks, taskId, statusFilter = null) {
subtask.status &&
subtask.status.toLowerCase() === statusFilter.toLowerCase()
);
// Return the filtered task and the original count
return { task: filteredTask, originalSubtaskCount: originalSubtaskCount };
taskResult = filteredTask;
originalSubtaskCount = originalSubtaskCount;
}
// Return original task and null count if no filter or no subtasks
return { task: task, originalSubtaskCount: null };
// If task found and complexityReport provided, add complexity data
if (taskResult && complexityReport) {
addComplexityToTask(taskResult, complexityReport);
}
// Return the found task and original subtask count
return { task: taskResult, originalSubtaskCount };
}
/**
@@ -508,6 +546,61 @@ function detectCamelCaseFlags(args) {
return camelCaseFlags;
}
/**
* Aggregates an array of telemetry objects into a single summary object.
* @param {Array<Object>} telemetryArray - Array of telemetryData objects.
* @param {string} overallCommandName - The name for the aggregated command.
* @returns {Object|null} Aggregated telemetry object or null if input is empty.
*/
function aggregateTelemetry(telemetryArray, overallCommandName) {
if (!telemetryArray || telemetryArray.length === 0) {
return null;
}
const aggregated = {
timestamp: new Date().toISOString(), // Use current time for aggregation time
userId: telemetryArray[0].userId, // Assume userId is consistent
commandName: overallCommandName,
modelUsed: 'Multiple', // Default if models vary
providerName: 'Multiple', // Default if providers vary
inputTokens: 0,
outputTokens: 0,
totalTokens: 0,
totalCost: 0,
currency: telemetryArray[0].currency || 'USD' // Assume consistent currency or default
};
const uniqueModels = new Set();
const uniqueProviders = new Set();
const uniqueCurrencies = new Set();
telemetryArray.forEach((item) => {
aggregated.inputTokens += item.inputTokens || 0;
aggregated.outputTokens += item.outputTokens || 0;
aggregated.totalCost += item.totalCost || 0;
uniqueModels.add(item.modelUsed);
uniqueProviders.add(item.providerName);
uniqueCurrencies.add(item.currency || 'USD');
});
aggregated.totalTokens = aggregated.inputTokens + aggregated.outputTokens;
aggregated.totalCost = parseFloat(aggregated.totalCost.toFixed(6)); // Fix precision
if (uniqueModels.size === 1) {
aggregated.modelUsed = [...uniqueModels][0];
}
if (uniqueProviders.size === 1) {
aggregated.providerName = [...uniqueProviders][0];
}
if (uniqueCurrencies.size > 1) {
aggregated.currency = 'Multiple'; // Mark if currencies actually differ
} else if (uniqueCurrencies.size === 1) {
aggregated.currency = [...uniqueCurrencies][0];
}
return aggregated;
}
// Export all utility functions and configuration
export {
LOG_LEVELS,
@@ -524,10 +617,12 @@ export {
findCycles,
toKebabCase,
detectCamelCaseFlags,
enableSilentMode,
disableSilentMode,
isSilentMode,
resolveEnvVariable,
enableSilentMode,
getTaskManager,
findProjectRoot
isSilentMode,
addComplexityToTask,
resolveEnvVariable,
findProjectRoot,
aggregateTelemetry
};

View File

@@ -1,7 +1,7 @@
{
"meta": {
"generatedAt": "2025-05-03T04:45:36.864Z",
"tasksAnalyzed": 36,
"generatedAt": "2025-05-17T22:29:22.179Z",
"tasksAnalyzed": 40,
"thresholdScore": 5,
"projectName": "Taskmaster",
"usedResearch": false
@@ -10,290 +10,322 @@
{
"taskId": 24,
"taskTitle": "Implement AI-Powered Test Generation Command",
"complexityScore": 8,
"complexityScore": 7,
"recommendedSubtasks": 5,
"expansionPrompt": "Expand the 'Implement AI-Powered Test Generation Command' task by detailing the specific steps required for AI prompt engineering, including data extraction, prompt formatting, and error handling.",
"reasoning": "Requires AI integration, complex logic, and thorough testing. Prompt engineering and API interaction add significant complexity."
"expansionPrompt": "Break down the implementation of the AI-powered test generation command into detailed subtasks covering: command structure setup, AI prompt engineering, test file generation logic, integration with Claude API, and comprehensive error handling.",
"reasoning": "This task involves complex integration with an AI service (Claude), requires sophisticated prompt engineering, and needs to generate structured code files. The existing 3 subtasks are a good start but could be expanded to include more detailed steps for AI integration, error handling, and test file formatting."
},
{
"taskId": 26,
"taskTitle": "Implement Context Foundation for AI Operations",
"complexityScore": 7,
"recommendedSubtasks": 6,
"expansionPrompt": "Expand the 'Implement Context Foundation for AI Operations' task by detailing the specific steps for integrating file reading, cursor rules, and basic context extraction into the Claude API prompts.",
"reasoning": "Involves modifying multiple commands and integrating different context sources. Error handling and backwards compatibility are crucial."
"complexityScore": 6,
"recommendedSubtasks": 4,
"expansionPrompt": "The current 4 subtasks for implementing the context foundation appear comprehensive. Consider if any additional subtasks are needed for testing, documentation, or integration with existing systems.",
"reasoning": "This task involves creating a foundation for context integration with several well-defined components. The existing 4 subtasks cover the main implementation areas (context-file flag, cursor rules integration, context extraction utility, and command handler updates). The complexity is moderate as it requires careful integration with existing systems but has clear requirements."
},
{
"taskId": 27,
"taskTitle": "Implement Context Enhancements for AI Operations",
"complexityScore": 8,
"recommendedSubtasks": 6,
"expansionPrompt": "Expand the 'Implement Context Enhancements for AI Operations' task by detailing the specific steps for code context extraction, task history integration, and PRD context integration, including parsing, summarization, and formatting.",
"reasoning": "Builds upon the previous task with more sophisticated context extraction and integration. Requires intelligent parsing and summarization."
"complexityScore": 7,
"recommendedSubtasks": 4,
"expansionPrompt": "The current 4 subtasks for implementing context enhancements appear well-structured. Consider if any additional subtasks are needed for testing, documentation, or performance optimization.",
"reasoning": "This task builds upon the foundation from Task #26 and adds more sophisticated context handling features. The 4 existing subtasks cover the main implementation areas (code context extraction, task history context, PRD context integration, and context formatting). The complexity is higher than the foundation task due to the need for intelligent context selection and optimization."
},
{
"taskId": 28,
"taskTitle": "Implement Advanced ContextManager System",
"complexityScore": 9,
"recommendedSubtasks": 7,
"expansionPrompt": "Expand the 'Implement Advanced ContextManager System' task by detailing the specific steps for creating the ContextManager class, implementing the optimization pipeline, and adding command interface enhancements, including caching and performance monitoring.",
"reasoning": "A comprehensive system requiring careful design, optimization, and testing. Involves complex algorithms and performance considerations."
},
{
"taskId": 32,
"taskTitle": "Implement \"learn\" Command for Automatic Cursor Rule Generation",
"complexityScore": 9,
"recommendedSubtasks": 10,
"expansionPrompt": "Expand the 'Implement \"learn\" Command for Automatic Cursor Rule Generation' task by detailing the specific steps for Cursor data analysis, rule management, and AI integration, including error handling and performance optimization.",
"reasoning": "Requires deep integration with Cursor's data, complex pattern analysis, and AI interaction. Significant error handling and performance optimization are needed."
"complexityScore": 8,
"recommendedSubtasks": 5,
"expansionPrompt": "The current 5 subtasks for implementing the advanced ContextManager system appear comprehensive. Consider if any additional subtasks are needed for testing, documentation, or backward compatibility with previous context implementations.",
"reasoning": "This task represents the most complex phase of the context implementation, requiring a sophisticated class design, optimization algorithms, and integration with multiple systems. The 5 existing subtasks cover the core implementation areas, but the complexity is high due to the need for intelligent context prioritization, token management, and performance monitoring."
},
{
"taskId": 40,
"taskTitle": "Implement 'plan' Command for Task Implementation Planning",
"complexityScore": 6,
"complexityScore": 5,
"recommendedSubtasks": 4,
"expansionPrompt": "Expand the 'Implement 'plan' Command for Task Implementation Planning' task by detailing the steps for retrieving task content, generating implementation plans with AI, and formatting the plan within XML tags.",
"reasoning": "Involves AI integration and requires careful formatting and error handling. Switching between Claude and Perplexity adds complexity."
"expansionPrompt": "The current 4 subtasks for implementing the 'plan' command appear well-structured. Consider if any additional subtasks are needed for testing, documentation, or integration with existing task management workflows.",
"reasoning": "This task involves creating a new command that leverages AI to generate implementation plans. The existing 4 subtasks cover the main implementation areas (retrieving task content, generating plans with AI, formatting in XML, and error handling). The complexity is moderate as it builds on existing patterns for task updates but requires careful AI integration."
},
{
"taskId": 41,
"taskTitle": "Implement Visual Task Dependency Graph in Terminal",
"complexityScore": 8,
"recommendedSubtasks": 8,
"expansionPrompt": "Expand the 'Implement Visual Task Dependency Graph in Terminal' task by detailing the steps for designing the graph rendering system, implementing layout algorithms, and handling circular dependencies and filtering options.",
"reasoning": "Requires complex graph algorithms and terminal rendering. Accessibility and performance are important considerations."
"recommendedSubtasks": 10,
"expansionPrompt": "The current 10 subtasks for implementing the visual task dependency graph appear comprehensive. Consider if any additional subtasks are needed for performance optimization with large graphs or additional visualization options.",
"reasoning": "This task involves creating a sophisticated visualization system for terminal display, which is inherently complex due to layout algorithms, ASCII/Unicode rendering, and handling complex dependency relationships. The 10 existing subtasks cover all major aspects of implementation, from CLI interface to accessibility features."
},
{
"taskId": 42,
"taskTitle": "Implement MCP-to-MCP Communication Protocol",
"complexityScore": 8,
"recommendedSubtasks": 7,
"expansionPrompt": "Expand the 'Implement MCP-to-MCP Communication Protocol' task by detailing the steps for defining the protocol, implementing the adapter pattern, and building the client module, including error handling and security considerations.",
"reasoning": "Requires designing a new protocol and implementing communication with external systems. Security and error handling are critical."
},
{
"taskId": 43,
"taskTitle": "Add Research Flag to Add-Task Command",
"complexityScore": 5,
"recommendedSubtasks": 3,
"expansionPrompt": "Expand the 'Add Research Flag to Add-Task Command' task by detailing the steps for updating the command parser, generating research subtasks, and linking them to the parent task.",
"reasoning": "Relatively straightforward, but requires careful handling of subtask generation and linking."
"complexityScore": 9,
"recommendedSubtasks": 8,
"expansionPrompt": "The current 8 subtasks for implementing the MCP-to-MCP communication protocol appear well-structured. Consider if any additional subtasks are needed for security hardening, performance optimization, or comprehensive documentation.",
"reasoning": "This task involves designing and implementing a complex communication protocol between different MCP tools and servers. It requires sophisticated adapter patterns, client-server architecture, and handling of multiple operational modes. The complexity is very high due to the need for standardization, security, and backward compatibility."
},
{
"taskId": 44,
"taskTitle": "Implement Task Automation with Webhooks and Event Triggers",
"complexityScore": 8,
"recommendedSubtasks": 7,
"expansionPrompt": "Expand the 'Implement Task Automation with Webhooks and Event Triggers' task by detailing the steps for implementing the webhook registration system, event system, and trigger definition interface, including security and error handling.",
"reasoning": "Requires designing a robust event system and integrating with external services. Security and error handling are critical."
"expansionPrompt": "The current 7 subtasks for implementing task automation with webhooks appear comprehensive. Consider if any additional subtasks are needed for security testing, rate limiting implementation, or webhook monitoring tools.",
"reasoning": "This task involves creating a sophisticated event system with webhooks for integration with external services. The complexity is high due to the need for secure authentication, reliable delivery mechanisms, and handling of various webhook formats and protocols. The existing subtasks cover the main implementation areas but security and monitoring could be emphasized more."
},
{
"taskId": 45,
"taskTitle": "Implement GitHub Issue Import Feature",
"complexityScore": 7,
"complexityScore": 6,
"recommendedSubtasks": 5,
"expansionPrompt": "Expand the 'Implement GitHub Issue Import Feature' task by detailing the steps for parsing the URL, fetching issue details from the GitHub API, and generating a well-formatted task.",
"reasoning": "Requires interacting with the GitHub API and handling various error conditions. Authentication adds complexity."
"expansionPrompt": "The current 5 subtasks for implementing the GitHub issue import feature appear well-structured. Consider if any additional subtasks are needed for handling GitHub API rate limiting, caching, or supporting additional issue metadata.",
"reasoning": "This task involves integrating with the GitHub API to import issues as tasks. The complexity is moderate as it requires API authentication, data mapping, and error handling. The existing 5 subtasks cover the main implementation areas from design to end-to-end implementation."
},
{
"taskId": 46,
"taskTitle": "Implement ICE Analysis Command for Task Prioritization",
"complexityScore": 7,
"recommendedSubtasks": 5,
"expansionPrompt": "Expand the 'Implement ICE Analysis Command for Task Prioritization' task by detailing the steps for calculating ICE scores, generating the report file, and implementing the CLI rendering.",
"reasoning": "Requires AI integration for scoring and careful formatting of the report. Integration with existing complexity reports adds complexity."
"expansionPrompt": "The current 5 subtasks for implementing the ICE analysis command appear comprehensive. Consider if any additional subtasks are needed for visualization of ICE scores or integration with other prioritization methods.",
"reasoning": "This task involves creating an AI-powered analysis system for task prioritization using the ICE methodology. The complexity is high due to the need for sophisticated scoring algorithms, AI integration, and report generation. The existing subtasks cover the main implementation areas from algorithm design to integration with existing systems."
},
{
"taskId": 47,
"taskTitle": "Enhance Task Suggestion Actions Card Workflow",
"complexityScore": 7,
"complexityScore": 6,
"recommendedSubtasks": 6,
"expansionPrompt": "Expand the 'Enhance Task Suggestion Actions Card Workflow' task by detailing the steps for implementing the task expansion, context addition, and task management phases, including UI/UX considerations.",
"reasoning": "Requires significant UI/UX work and careful state management. Integration with existing functionality is crucial."
"expansionPrompt": "The current 6 subtasks for enhancing the task suggestion actions card workflow appear well-structured. Consider if any additional subtasks are needed for user testing, accessibility improvements, or performance optimization.",
"reasoning": "This task involves redesigning the UI workflow for task expansion and management. The complexity is moderate as it requires careful UX design and state management but builds on existing components. The 6 existing subtasks cover the main implementation areas from design to testing."
},
{
"taskId": 48,
"taskTitle": "Refactor Prompts into Centralized Structure",
"complexityScore": 5,
"complexityScore": 4,
"recommendedSubtasks": 3,
"expansionPrompt": "Expand the 'Refactor Prompts into Centralized Structure' task by detailing the steps for creating the 'prompts' directory, extracting prompts into individual files, and updating functions to import them.",
"reasoning": "Primarily a refactoring task, but requires careful attention to detail to avoid breaking existing functionality."
"expansionPrompt": "The current 3 subtasks for refactoring prompts into a centralized structure appear appropriate. Consider if any additional subtasks are needed for prompt versioning, documentation, or testing.",
"reasoning": "This task involves a straightforward refactoring to improve code organization. The complexity is relatively low as it primarily involves moving code rather than creating new functionality. The 3 existing subtasks cover the main implementation areas from directory structure to integration."
},
{
"taskId": 49,
"taskTitle": "Implement Code Quality Analysis Command",
"complexityScore": 8,
"recommendedSubtasks": 6,
"expansionPrompt": "Expand the 'Implement Code Quality Analysis Command' task by detailing the steps for pattern recognition, best practice verification, and improvement recommendations, including AI integration and task creation.",
"reasoning": "Requires complex code analysis and AI integration. Generating actionable recommendations adds complexity."
"expansionPrompt": "The current 6 subtasks for implementing the code quality analysis command appear comprehensive. Consider if any additional subtasks are needed for performance optimization with large codebases or integration with existing code quality tools.",
"reasoning": "This task involves creating a sophisticated code analysis system with pattern recognition, best practice verification, and AI-powered recommendations. The complexity is high due to the need for code parsing, complex analysis algorithms, and integration with AI services. The existing subtasks cover the main implementation areas from algorithm design to user interface."
},
{
"taskId": 50,
"taskTitle": "Implement Test Coverage Tracking System by Task",
"complexityScore": 9,
"recommendedSubtasks": 7,
"expansionPrompt": "Expand the 'Implement Test Coverage Tracking System by Task' task by detailing the steps for creating the tests.json file structure, developing the coverage report parser, and implementing the CLI commands and AI-powered test generation system.",
"reasoning": "A comprehensive system requiring deep integration with testing tools and AI. Maintaining bidirectional relationships adds complexity."
"recommendedSubtasks": 5,
"expansionPrompt": "The current 5 subtasks for implementing the test coverage tracking system appear well-structured. Consider if any additional subtasks are needed for integration with CI/CD systems, performance optimization, or visualization tools.",
"reasoning": "This task involves creating a complex system that maps test coverage to specific tasks and subtasks. The complexity is very high due to the need for sophisticated data structures, integration with coverage tools, and AI-powered test generation. The existing subtasks are comprehensive and cover the main implementation areas from data structure design to AI integration."
},
{
"taskId": 51,
"taskTitle": "Implement Perplexity Research Command",
"complexityScore": 7,
"complexityScore": 6,
"recommendedSubtasks": 5,
"expansionPrompt": "Expand the 'Implement Perplexity Research Command' task by detailing the steps for creating the Perplexity API client, implementing task context extraction, and building the CLI interface.",
"reasoning": "Requires API integration and careful formatting of the research results. Caching adds complexity."
"expansionPrompt": "The current 5 subtasks for implementing the Perplexity research command appear comprehensive. Consider if any additional subtasks are needed for caching optimization, result formatting, or integration with other research tools.",
"reasoning": "This task involves creating a new command that integrates with the Perplexity AI API for research. The complexity is moderate as it requires API integration, context extraction, and result formatting. The 5 existing subtasks cover the main implementation areas from API client to caching system."
},
{
"taskId": 52,
"taskTitle": "Implement Task Suggestion Command for CLI",
"complexityScore": 7,
"complexityScore": 6,
"recommendedSubtasks": 5,
"expansionPrompt": "Expand the 'Implement Task Suggestion Command for CLI' task by detailing the steps for collecting existing task data, generating task suggestions with AI, and implementing the interactive CLI interface.",
"reasoning": "Requires AI integration and careful design of the interactive interface. Handling various flag combinations adds complexity."
"expansionPrompt": "The current 5 subtasks for implementing the task suggestion command appear well-structured. Consider if any additional subtasks are needed for suggestion quality evaluation, user feedback collection, or integration with existing task workflows.",
"reasoning": "This task involves creating a new CLI command that generates contextually relevant task suggestions using AI. The complexity is moderate as it requires AI integration, context collection, and interactive CLI interfaces. The existing subtasks cover the main implementation areas from data collection to user interface."
},
{
"taskId": 53,
"taskTitle": "Implement Subtask Suggestion Feature for Parent Tasks",
"complexityScore": 7,
"complexityScore": 6,
"recommendedSubtasks": 6,
"expansionPrompt": "Expand the 'Implement Subtask Suggestion Feature for Parent Tasks' task by detailing the steps for validating parent tasks, gathering context, generating subtask suggestions with AI, and implementing the interactive CLI interface.",
"reasoning": "Requires AI integration and careful design of the interactive interface. Linking subtasks to parent tasks adds complexity."
"expansionPrompt": "The current 6 subtasks for implementing the subtask suggestion feature appear comprehensive. Consider if any additional subtasks are needed for suggestion quality metrics, user feedback collection, or performance optimization.",
"reasoning": "This task involves creating a feature that suggests contextually relevant subtasks for parent tasks. The complexity is moderate as it builds on existing task management systems but requires sophisticated AI integration and context analysis. The 6 existing subtasks cover the main implementation areas from validation to testing."
},
{
"taskId": 55,
"taskTitle": "Implement Positional Arguments Support for CLI Commands",
"complexityScore": 7,
"complexityScore": 5,
"recommendedSubtasks": 5,
"expansionPrompt": "Expand the 'Implement Positional Arguments Support for CLI Commands' task by detailing the steps for updating the argument parsing logic, defining the positional argument order, and handling edge cases.",
"reasoning": "Requires careful modification of the command parsing logic and ensuring backward compatibility. Handling edge cases adds complexity."
"expansionPrompt": "The current 5 subtasks for implementing positional arguments support appear well-structured. Consider if any additional subtasks are needed for backward compatibility testing, documentation updates, or user experience improvements.",
"reasoning": "This task involves modifying the command parsing logic to support positional arguments alongside the existing flag-based syntax. The complexity is moderate as it requires careful handling of different argument styles and edge cases. The 5 existing subtasks cover the main implementation areas from analysis to documentation."
},
{
"taskId": 57,
"taskTitle": "Enhance Task-Master CLI User Experience and Interface",
"complexityScore": 7,
"recommendedSubtasks": 6,
"expansionPrompt": "Expand the 'Enhance Task-Master CLI User Experience and Interface' task by detailing the steps for log management, visual enhancements, interactive elements, and output formatting.",
"reasoning": "Requires significant UI/UX work and careful consideration of different terminal environments. Reducing verbose logging adds complexity."
"expansionPrompt": "The current 6 subtasks for enhancing the CLI user experience appear comprehensive. Consider if any additional subtasks are needed for accessibility testing, internationalization, or performance optimization.",
"reasoning": "This task involves a significant overhaul of the CLI interface to improve user experience. The complexity is high due to the breadth of changes (logging, visual elements, interactive components, etc.) and the need for consistent design across all commands. The 6 existing subtasks cover the main implementation areas from log management to help systems."
},
{
"taskId": 60,
"taskTitle": "Implement Mentor System with Round-Table Discussion Feature",
"complexityScore": 8,
"recommendedSubtasks": 7,
"expansionPrompt": "Expand the 'Implement Mentor System with Round-Table Discussion Feature' task by detailing the steps for mentor management, round-table discussion implementation, and integration with the task system, including LLM integration.",
"reasoning": "Requires complex AI simulation and careful formatting of the discussion output. Integrating with the task system adds complexity."
},
{
"taskId": 61,
"taskTitle": "Implement Flexible AI Model Management",
"complexityScore": 9,
"recommendedSubtasks": 8,
"expansionPrompt": "Expand the 'Implement Flexible AI Model Management' task by detailing the steps for creating the configuration management module, implementing the CLI command parser, and integrating the Vercel AI SDK.",
"reasoning": "Requires deep integration with multiple AI models and careful management of API keys and configuration options. Vercel AI SDK integration adds complexity."
"expansionPrompt": "The current 7 subtasks for implementing the mentor system appear well-structured. Consider if any additional subtasks are needed for mentor personality consistency, discussion quality evaluation, or performance optimization with multiple mentors.",
"reasoning": "This task involves creating a sophisticated mentor simulation system with round-table discussions. The complexity is high due to the need for personality simulation, complex LLM integration, and structured discussion management. The 7 existing subtasks cover the main implementation areas from architecture to testing."
},
{
"taskId": 62,
"taskTitle": "Add --simple Flag to Update Commands for Direct Text Input",
"complexityScore": 5,
"recommendedSubtasks": 4,
"expansionPrompt": "Expand the 'Add --simple Flag to Update Commands for Direct Text Input' task by detailing the steps for updating the command parsers, implementing the conditional logic, and formatting the user input with a timestamp.",
"reasoning": "Relatively straightforward, but requires careful attention to formatting and ensuring consistency with AI-processed updates."
"complexityScore": 4,
"recommendedSubtasks": 8,
"expansionPrompt": "The current 8 subtasks for implementing the --simple flag appear comprehensive. Consider if any additional subtasks are needed for user experience testing or documentation updates.",
"reasoning": "This task involves adding a simple flag option to bypass AI processing for updates. The complexity is relatively low as it primarily involves modifying existing command handlers and adding a flag. The 8 existing subtasks are very detailed and cover all aspects of implementation from command parsing to testing."
},
{
"taskId": 63,
"taskTitle": "Add pnpm Support for the Taskmaster Package",
"complexityScore": 7,
"recommendedSubtasks": 6,
"expansionPrompt": "Expand the 'Add pnpm Support for the Taskmaster Package' task by detailing the steps for updating the documentation, ensuring package scripts compatibility, and testing the installation and operation with pnpm.",
"reasoning": "Requires careful attention to detail to ensure compatibility with pnpm's execution model. Testing and documentation are crucial."
"complexityScore": 5,
"recommendedSubtasks": 8,
"expansionPrompt": "The current 8 subtasks for adding pnpm support appear comprehensive. Consider if any additional subtasks are needed for CI/CD integration, performance comparison, or documentation updates.",
"reasoning": "This task involves ensuring the package works correctly with pnpm as an alternative package manager. The complexity is moderate as it requires careful testing of installation processes and scripts across different environments. The 8 existing subtasks cover all major aspects from documentation to binary verification."
},
{
"taskId": 64,
"taskTitle": "Add Yarn Support for Taskmaster Installation",
"complexityScore": 7,
"recommendedSubtasks": 6,
"expansionPrompt": "Expand the 'Add Yarn Support for Taskmaster Installation' task by detailing the steps for updating package.json, adding Yarn-specific configuration files, and testing the installation and operation with Yarn.",
"reasoning": "Requires careful attention to detail to ensure compatibility with Yarn's execution model. Testing and documentation are crucial."
"complexityScore": 5,
"recommendedSubtasks": 9,
"expansionPrompt": "The current 9 subtasks for adding Yarn support appear comprehensive. Consider if any additional subtasks are needed for performance testing, CI/CD integration, or compatibility with different Yarn versions.",
"reasoning": "This task involves ensuring the package works correctly with Yarn as an alternative package manager. The complexity is moderate as it requires careful testing of installation processes and scripts across different environments. The 9 existing subtasks are very detailed and cover all aspects from configuration to testing."
},
{
"taskId": 65,
"taskTitle": "Add Bun Support for Taskmaster Installation",
"complexityScore": 7,
"complexityScore": 6,
"recommendedSubtasks": 6,
"expansionPrompt": "Expand the 'Add Bun Support for Taskmaster Installation' task by detailing the steps for updating the installation scripts, testing the installation and operation with Bun, and updating the documentation.",
"reasoning": "Requires careful attention to detail to ensure compatibility with Bun's execution model. Testing and documentation are crucial."
},
{
"taskId": 66,
"taskTitle": "Support Status Filtering in Show Command for Subtasks",
"complexityScore": 5,
"recommendedSubtasks": 4,
"expansionPrompt": "Expand the 'Support Status Filtering in Show Command for Subtasks' task by detailing the steps for updating the command parser, modifying the show command handler, and updating the help documentation.",
"reasoning": "Relatively straightforward, but requires careful handling of status validation and filtering."
"expansionPrompt": "The current 6 subtasks for adding Bun support appear well-structured. Consider if any additional subtasks are needed for handling Bun-specific issues, performance testing, or documentation updates.",
"reasoning": "This task involves adding support for the newer Bun package manager. The complexity is slightly higher than the other package manager tasks due to Bun's differences from Node.js and potential compatibility issues. The 6 existing subtasks cover the main implementation areas from research to documentation."
},
{
"taskId": 67,
"taskTitle": "Add CLI JSON output and Cursor keybindings integration",
"complexityScore": 7,
"recommendedSubtasks": 6,
"expansionPrompt": "Expand the 'Add CLI JSON output and Cursor keybindings integration' task by detailing the steps for implementing the JSON output logic, creating the install-keybindings command structure, and handling keybinding file manipulation.",
"reasoning": "Requires careful formatting of the JSON output and handling of file system operations. OS detection adds complexity."
"complexityScore": 5,
"recommendedSubtasks": 5,
"expansionPrompt": "The current 5 subtasks for implementing JSON output and Cursor keybindings appear well-structured. Consider if any additional subtasks are needed for testing across different operating systems, documentation updates, or user experience improvements.",
"reasoning": "This task involves two distinct features: adding JSON output to CLI commands and creating a keybindings installation command. The complexity is moderate as it requires careful handling of different output formats and OS-specific file paths. The 5 existing subtasks cover the main implementation areas for both features."
},
{
"taskId": 68,
"taskTitle": "Ability to create tasks without parsing PRD",
"complexityScore": 3,
"recommendedSubtasks": 2,
"expansionPrompt": "Expand the 'Ability to create tasks without parsing PRD' task by detailing the steps for creating tasks without a PRD.",
"reasoning": "Simple task to allow task creation without a PRD."
"expansionPrompt": "The current 2 subtasks for implementing task creation without PRD appear appropriate. Consider if any additional subtasks are needed for validation, error handling, or integration with existing task management workflows.",
"reasoning": "This task involves a relatively simple modification to allow task creation without requiring a PRD document. The complexity is low as it primarily involves creating a form interface and saving functionality. The 2 existing subtasks cover the main implementation areas of UI design and data saving."
},
{
"taskId": 69,
"taskTitle": "Enhance Analyze Complexity for Specific Task IDs",
"complexityScore": 6,
"complexityScore": 5,
"recommendedSubtasks": 4,
"expansionPrompt": "Expand the 'Enhance Analyze Complexity for Specific Task IDs' task by detailing the steps for modifying the core logic, updating the CLI, and updating the MCP tool.",
"reasoning": "Requires modifying existing functionality and ensuring compatibility with both CLI and MCP."
"expansionPrompt": "The current 4 subtasks for enhancing the analyze-complexity feature appear well-structured. Consider if any additional subtasks are needed for performance optimization with large task sets or visualization improvements.",
"reasoning": "This task involves modifying the existing analyze-complexity feature to support analyzing specific task IDs and updating reports. The complexity is moderate as it requires careful handling of report merging and filtering logic. The 4 existing subtasks cover the main implementation areas from core logic to testing."
},
{
"taskId": 70,
"taskTitle": "Implement 'diagram' command for Mermaid diagram generation",
"complexityScore": 6,
"recommendedSubtasks": 4,
"expansionPrompt": "Expand the 'Implement 'diagram' command for Mermaid diagram generation' task by detailing the steps for creating the command, generating the Mermaid diagram, and handling different output options.",
"reasoning": "Requires generating Mermaid diagrams and handling different output options."
"expansionPrompt": "The current 4 subtasks for implementing the 'diagram' command appear well-structured. Consider if any additional subtasks are needed for handling large dependency graphs, additional output formats, or integration with existing visualization tools.",
"reasoning": "This task involves creating a new command that generates Mermaid diagrams to visualize task dependencies. The complexity is moderate as it requires parsing task relationships, generating proper Mermaid syntax, and handling various output options. The 4 existing subtasks cover the main implementation areas from interface design to documentation."
},
{
"taskId": 72,
"taskTitle": "Implement PDF Generation for Project Progress and Dependency Overview",
"complexityScore": 8,
"recommendedSubtasks": 6,
"expansionPrompt": "Expand the 'Implement PDF Generation for Project Progress and Dependency Overview' task by detailing the steps for summarizing project progress, visualizing the dependency chain, and generating the PDF document.",
"reasoning": "Requires integrating with the diagram command and using a PDF generation library. Handling large dependency chains adds complexity."
},
{
"taskId": 73,
"taskTitle": "Implement Custom Model ID Support for Ollama/OpenRouter",
"complexityScore": 7,
"recommendedSubtasks": 5,
"expansionPrompt": "Expand the 'Implement Custom Model ID Support for Ollama/OpenRouter' task by detailing the steps for modifying the CLI, implementing the interactive setup, and handling validation and warnings.",
"reasoning": "Requires integrating with external APIs and handling different model types. Validation and warnings are crucial."
"recommendedSubtasks": 6,
"expansionPrompt": "The current 6 subtasks for implementing PDF generation appear comprehensive. Consider if any additional subtasks are needed for handling large projects, additional visualization options, or integration with existing reporting tools.",
"reasoning": "This task involves creating a feature to generate PDF reports of project progress and dependency visualization. The complexity is high due to the need for PDF generation, data collection, and visualization integration. The 6 existing subtasks cover the main implementation areas from library selection to export options."
},
{
"taskId": 75,
"taskTitle": "Integrate Google Search Grounding for Research Role",
"complexityScore": 6,
"complexityScore": 5,
"recommendedSubtasks": 4,
"expansionPrompt": "Expand the 'Integrate Google Search Grounding for Research Role' task by detailing the steps for modifying the AI service layer, implementing the conditional logic, and updating the supported models.",
"reasoning": "Requires conditional logic and integration with the Google Search Grounding API."
"expansionPrompt": "The current 4 subtasks for integrating Google Search Grounding appear well-structured. Consider if any additional subtasks are needed for testing with different query types, error handling, or performance optimization.",
"reasoning": "This task involves updating the AI service layer to enable Google Search Grounding for research roles. The complexity is moderate as it requires careful integration with the existing AI service architecture and conditional logic. The 4 existing subtasks cover the main implementation areas from service layer modification to testing."
},
{
"taskId": 76,
"taskTitle": "Develop E2E Test Framework for Taskmaster MCP Server (FastMCP over stdio)",
"complexityScore": 9,
"complexityScore": 8,
"recommendedSubtasks": 7,
"expansionPrompt": "Expand the 'Develop E2E Test Framework for Taskmaster MCP Server (FastMCP over stdio)' task by detailing the steps for launching the FastMCP server, implementing the message protocol handler, and developing the request/response correlation mechanism.",
"reasoning": "Requires complex system integration and robust error handling. Designing a comprehensive test framework adds complexity."
"expansionPrompt": "The current 7 subtasks for developing the E2E test framework appear comprehensive. Consider if any additional subtasks are needed for test result reporting, CI/CD integration, or performance benchmarking.",
"reasoning": "This task involves creating a sophisticated end-to-end testing framework for the MCP server. The complexity is high due to the need for subprocess management, protocol handling, and robust test case definition. The 7 existing subtasks cover the main implementation areas from architecture to documentation."
},
{
"taskId": 77,
"taskTitle": "Implement AI Usage Telemetry for Taskmaster (with external analytics endpoint)",
"complexityScore": 7,
"recommendedSubtasks": 18,
"expansionPrompt": "The current 18 subtasks for implementing AI usage telemetry appear very comprehensive. Consider if any additional subtasks are needed for security hardening, privacy compliance, or user feedback collection.",
"reasoning": "This task involves creating a telemetry system to track AI usage metrics. The complexity is high due to the need for secure data transmission, comprehensive data collection, and integration across multiple commands. The 18 existing subtasks are extremely detailed and cover all aspects of implementation from core utility to provider-specific updates."
},
{
"taskId": 80,
"taskTitle": "Implement Unique User ID Generation and Storage During Installation",
"complexityScore": 4,
"recommendedSubtasks": 5,
"expansionPrompt": "The current 5 subtasks for implementing unique user ID generation appear well-structured. Consider if any additional subtasks are needed for privacy compliance, security auditing, or integration with the telemetry system.",
"reasoning": "This task involves generating and storing a unique user identifier during installation. The complexity is relatively low as it primarily involves UUID generation and configuration file management. The 5 existing subtasks cover the main implementation areas from script structure to documentation."
},
{
"taskId": 81,
"taskTitle": "Task #81: Implement Comprehensive Local Telemetry System with Future Server Integration Capability",
"complexityScore": 8,
"recommendedSubtasks": 6,
"expansionPrompt": "The current 6 subtasks for implementing the comprehensive local telemetry system appear well-structured. Consider if any additional subtasks are needed for data migration, storage optimization, or visualization tools.",
"reasoning": "This task involves expanding the telemetry system to capture additional metrics and implement local storage with future server integration capability. The complexity is high due to the breadth of data collection, storage requirements, and privacy considerations. The 6 existing subtasks cover the main implementation areas from data collection to user-facing benefits."
},
{
"taskId": 82,
"taskTitle": "Update supported-models.json with token limit fields",
"complexityScore": 3,
"recommendedSubtasks": 1,
"expansionPrompt": "This task appears straightforward enough to be implemented without further subtasks. Focus on researching accurate token limit values for each model and ensuring backward compatibility.",
"reasoning": "This task involves a simple update to the supported-models.json file to include new token limit fields. The complexity is low as it primarily involves research and data entry. No subtasks are necessary as the task is well-defined and focused."
},
{
"taskId": 83,
"taskTitle": "Update config-manager.js defaults and getters",
"complexityScore": 4,
"recommendedSubtasks": 1,
"expansionPrompt": "This task appears straightforward enough to be implemented without further subtasks. Focus on updating the DEFAULTS object and related getter functions while maintaining backward compatibility.",
"reasoning": "This task involves updating the config-manager.js module to replace maxTokens with more specific token limit fields. The complexity is relatively low as it primarily involves modifying existing code rather than creating new functionality. No subtasks are necessary as the task is well-defined and focused."
},
{
"taskId": 84,
"taskTitle": "Implement token counting utility",
"complexityScore": 5,
"recommendedSubtasks": 1,
"expansionPrompt": "This task appears well-defined enough to be implemented without further subtasks. Focus on implementing accurate token counting for different models and proper fallback mechanisms.",
"reasoning": "This task involves creating a utility function to count tokens for different AI models. The complexity is moderate as it requires integration with the tiktoken library and handling different tokenization schemes. No subtasks are necessary as the task is well-defined and focused."
},
{
"taskId": 85,
"taskTitle": "Update ai-services-unified.js for dynamic token limits",
"complexityScore": 6,
"recommendedSubtasks": 1,
"expansionPrompt": "This task appears well-defined enough to be implemented without further subtasks. Focus on implementing dynamic token limit adjustment based on input length and model capabilities.",
"reasoning": "This task involves modifying the AI service runner to use the new token counting utility and dynamically adjust output token limits. The complexity is moderate to high as it requires careful integration with existing code and handling various edge cases. No subtasks are necessary as the task is well-defined and focused."
},
{
"taskId": 86,
"taskTitle": "Update .taskmasterconfig schema and user guide",
"complexityScore": 4,
"recommendedSubtasks": 1,
"expansionPrompt": "This task appears straightforward enough to be implemented without further subtasks. Focus on creating clear migration guidance and updating documentation.",
"reasoning": "This task involves creating a migration guide for users to update their configuration files and documenting the new token limit options. The complexity is relatively low as it primarily involves documentation and schema validation. No subtasks are necessary as the task is well-defined and focused."
},
{
"taskId": 87,
"taskTitle": "Implement validation and error handling",
"complexityScore": 5,
"recommendedSubtasks": 1,
"expansionPrompt": "This task appears well-defined enough to be implemented without further subtasks. Focus on comprehensive validation and helpful error messages throughout the system.",
"reasoning": "This task involves adding validation and error handling for token limits throughout the system. The complexity is moderate as it requires careful integration with multiple components and creating helpful error messages. No subtasks are necessary as the task is well-defined and focused."
}
]
}