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revamping readme (#522)

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celgost
2025-05-24 17:21:15 +02:00
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parent d1e45ff50e
commit b60e1cf835
4 changed files with 365 additions and 13 deletions
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40
.github/workflows/update-models-md.yml vendored Normal file
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name: Update models.md from supported-models.json
on:
push:
branches:
- main
- next
paths:
- 'scripts/modules/supported-models.json'
- 'docs/scripts/models-json-to-markdown.js'
jobs:
update_markdown:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Set up Node.js
uses: actions/setup-node@v4
with:
node-version: 20
- name: Run transformation script
run: node docs/scripts/models-json-to-markdown.js
- name: Format Markdown with Prettier
run: npx prettier --write docs/models.md
- name: Stage docs/models.md
run: git add docs/models.md
- name: Commit & Push docs/models.md
uses: actions-js/push@master
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
branch: ${{ github.ref_name }}
message: 'docs: Auto-update and format models.md'
author_name: 'github-actions[bot]'
author_email: 'github-actions[bot]@users.noreply.github.com'

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README.md
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@@ -28,13 +28,22 @@ Using the research model is optional but highly recommended. You will need at le
## Quick Start ## Quick Start
### Option 1 | MCP (Recommended): ### Option 1: MCP (Recommended)
MCP (Model Control Protocol) provides the easiest way to get started with Task Master directly in your editor. MCP (Model Control Protocol) lets you run Task Master directly from your editor.
1. **Add the MCP config to your editor** (Cursor recommended, but it works with other text editors): #### 1. Add your MCP config at the following path depending on your editor
```json | Editor | Scope | Linux/macOS Path | Windows Path | Key |
| ------------ | ------- | ------------------------------------- | ------------------------------------------------- | ------------ |
| **Cursor** | Global | `~/.cursor/mcp.json` | `%USERPROFILE%\.cursor\mcp.json` | `mcpServers` |
| | Project | `<project_folder>/.cursor/mcp.json` | `<project_folder>\.cursor\mcp.json` | `mcpServers` |
| **Windsurf** | Global | `~/.codeium/windsurf/mcp_config.json` | `%USERPROFILE%\.codeium\windsurf\mcp_config.json` | `mcpServers` |
| **VS Code** | Project | `<project_folder>/.vscode/mcp.json` | `<project_folder>\.vscode\mcp.json` | `servers` |
##### Cursor & Windsurf (`mcpServers`)
```jsonc
{ {
"mcpServers": { "mcpServers": {
"taskmaster-ai": { "taskmaster-ai": {
@@ -56,23 +65,75 @@ MCP (Model Control Protocol) provides the easiest way to get started with Task M
} }
``` ```
2. **Enable the MCP** in your editor > 🔑 Replace `YOUR_…_KEY_HERE` with your real API keys. You can remove keys you don't use.
3. **Prompt the AI** to initialize Task Master: ##### VS Code (`servers` + `type`)
``` ```jsonc
Can you please initialize taskmaster-ai into my project? {
"servers": {
"taskmaster-ai": {
"command": "npx",
"args": ["-y", "--package=task-master-ai", "task-master-ai"],
"env": {
"ANTHROPIC_API_KEY": "YOUR_ANTHROPIC_API_KEY_HERE",
"PERPLEXITY_API_KEY": "YOUR_PERPLEXITY_API_KEY_HERE",
"OPENAI_API_KEY": "YOUR_OPENAI_KEY_HERE",
"GOOGLE_API_KEY": "YOUR_GOOGLE_KEY_HERE",
"MISTRAL_API_KEY": "YOUR_MISTRAL_KEY_HERE",
"OPENROUTER_API_KEY": "YOUR_OPENROUTER_KEY_HERE",
"XAI_API_KEY": "YOUR_XAI_KEY_HERE",
"AZURE_OPENAI_API_KEY": "YOUR_AZURE_KEY_HERE"
},
"type": "stdio"
}
}
}
``` ```
4. **Use common commands** directly through your AI assistant: > 🔑 Replace `YOUR_…_KEY_HERE` with your real API keys. You can remove keys you don't use.
#### 2. (Cursor-only) Enable Taskmaster MCP
Open Cursor Settings (Ctrl+Shift+J) ➡ Click on MCP tab on the left ➡ Enable task-master-ai with the toggle
#### 3. (Optional) Configure the models you want to use
In your editor’s AI chat pane, say:
```txt ```txt
Can you parse my PRD at scripts/prd.txt? Change the main, research and fallback models to <model_name>, <model_name> and <model_name> respectively.
What's the next task I should work on?
Can you help me implement task 3?
Can you help me expand task 4?
``` ```
[Table of available models](docs/models.md)
#### 4. Initialize Task Master
In your editor’s AI chat pane, say:
```txt
Initialize taskmaster-ai in my project
```
#### 5. Make sure you have a PRD in `<project_folder>/scripts/prd.txt`
An example of a PRD is located into `<project_folder>/scripts/example_prd.txt`.
**Always start with a detailed PRD.**
The more detailed your PRD, the better the generated tasks will be.
#### 6. Common Commands
Use your AI assistant to:
- Parse requirements: `Can you parse my PRD at scripts/prd.txt?`
- Plan next step: `What’s the next task I should work on?`
- Implement a task: `Can you help me implement task 3?`
- Expand a task: `Can you help me expand task 4?`
[More examples on how to use Task Master in chat](docs/examples.md)
### Option 2: Using Command Line ### Option 2: Using Command Line
#### Installation #### Installation

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docs/models.md Normal file
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# Available Models as of May 16, 2025
## Main Models
| Provider | Model Name | SWE Score | Input Cost | Output Cost |
| ---------- | --------------------------------------------- | --------- | ---------- | ----------- |
| anthropic | claude-3-7-sonnet-20250219 | 0.623 | 3 | 15 |
| anthropic | claude-3-5-sonnet-20241022 | 0.49 | 3 | 15 |
| openai | gpt-4o | 0.332 | 2.5 | 10 |
| openai | o1 | 0.489 | 15 | 60 |
| openai | o3 | 0.5 | 10 | 40 |
| openai | o3-mini | 0.493 | 1.1 | 4.4 |
| openai | o4-mini | 0.45 | 1.1 | 4.4 |
| openai | o1-mini | 0.4 | 1.1 | 4.4 |
| openai | o1-pro | — | 150 | 600 |
| openai | gpt-4-5-preview | 0.38 | 75 | 150 |
| openai | gpt-4-1-mini | — | 0.4 | 1.6 |
| openai | gpt-4-1-nano | — | 0.1 | 0.4 |
| openai | gpt-4o-mini | 0.3 | 0.15 | 0.6 |
| google | gemini-2.5-pro-exp-03-25 | 0.638 | — | — |
| google | gemini-2.5-flash-preview-04-17 | — | — | — |
| google | gemini-2.0-flash | 0.754 | 0.15 | 0.6 |
| google | gemini-2.0-flash-thinking-experimental | 0.754 | 0.15 | 0.6 |
| google | gemini-2.0-pro | — | — | — |
| perplexity | sonar-reasoning-pro | 0.211 | 2 | 8 |
| perplexity | sonar-reasoning | 0.211 | 1 | 5 |
| xai | grok-3 | — | 3 | 15 |
| xai | grok-3-fast | — | 5 | 25 |
| ollama | gemma3:27b | — | 0 | 0 |
| ollama | gemma3:12b | — | 0 | 0 |
| ollama | qwq | — | 0 | 0 |
| ollama | deepseek-r1 | — | 0 | 0 |
| ollama | mistral-small3.1 | — | 0 | 0 |
| ollama | llama3.3 | — | 0 | 0 |
| ollama | phi4 | — | 0 | 0 |
| openrouter | google/gemini-2.0-flash-001 | — | 0.1 | 0.4 |
| openrouter | google/gemini-2.5-pro-exp-03-25 | — | 0 | 0 |
| openrouter | deepseek/deepseek-chat-v3-0324:free | — | 0 | 0 |
| openrouter | deepseek/deepseek-chat-v3-0324 | — | 0.27 | 1.1 |
| openrouter | deepseek/deepseek-r1:free | — | 0 | 0 |
| openrouter | microsoft/mai-ds-r1:free | — | 0 | 0 |
| openrouter | google/gemini-2.5-pro-preview-03-25 | — | 1.25 | 10 |
| openrouter | google/gemini-2.5-flash-preview | — | 0.15 | 0.6 |
| openrouter | google/gemini-2.5-flash-preview:thinking | — | 0.15 | 3.5 |
| openrouter | openai/o3 | — | 10 | 40 |
| openrouter | openai/o4-mini | 0.45 | 1.1 | 4.4 |
| openrouter | openai/o4-mini-high | — | 1.1 | 4.4 |
| openrouter | openai/o1-pro | — | 150 | 600 |
| openrouter | meta-llama/llama-3.3-70b-instruct | — | 120 | 600 |
| openrouter | google/gemma-3-12b-it:free | — | 0 | 0 |
| openrouter | google/gemma-3-12b-it | — | 50 | 100 |
| openrouter | google/gemma-3-27b-it:free | — | 0 | 0 |
| openrouter | google/gemma-3-27b-it | — | 100 | 200 |
| openrouter | qwen/qwq-32b:free | — | 0 | 0 |
| openrouter | qwen/qwq-32b | — | 150 | 200 |
| openrouter | qwen/qwen-max | — | 1.6 | 6.4 |
| openrouter | qwen/qwen-turbo | — | 0.05 | 0.2 |
| openrouter | mistralai/mistral-small-3.1-24b-instruct:free | — | 0 | 0 |
| openrouter | mistralai/mistral-small-3.1-24b-instruct | — | 0.1 | 0.3 |
| openrouter | thudm/glm-4-32b:free | — | 0 | 0 |
## Research Models
| Provider | Model Name | SWE Score | Input Cost | Output Cost |
| ---------- | -------------------------- | --------- | ---------- | ----------- |
| openai | gpt-4o-search-preview | 0.33 | 2.5 | 10 |
| openai | gpt-4o-mini-search-preview | 0.3 | 0.15 | 0.6 |
| perplexity | sonar-pro | — | 3 | 15 |
| perplexity | sonar | — | 1 | 1 |
| perplexity | deep-research | 0.211 | 2 | 8 |
| xai | grok-3 | — | 3 | 15 |
| xai | grok-3-fast | — | 5 | 25 |
## Fallback Models
| Provider | Model Name | SWE Score | Input Cost | Output Cost |
| ---------- | --------------------------------------------- | --------- | ---------- | ----------- |
| anthropic | claude-3-7-sonnet-20250219 | 0.623 | 3 | 15 |
| anthropic | claude-3-5-sonnet-20241022 | 0.49 | 3 | 15 |
| openai | gpt-4o | 0.332 | 2.5 | 10 |
| openai | o3 | 0.5 | 10 | 40 |
| openai | o4-mini | 0.45 | 1.1 | 4.4 |
| google | gemini-2.5-pro-exp-03-25 | 0.638 | — | — |
| google | gemini-2.5-flash-preview-04-17 | — | — | — |
| google | gemini-2.0-flash | 0.754 | 0.15 | 0.6 |
| google | gemini-2.0-flash-thinking-experimental | 0.754 | 0.15 | 0.6 |
| google | gemini-2.0-pro | — | — | — |
| perplexity | sonar-reasoning-pro | 0.211 | 2 | 8 |
| perplexity | sonar-reasoning | 0.211 | 1 | 5 |
| xai | grok-3 | — | 3 | 15 |
| xai | grok-3-fast | — | 5 | 25 |
| ollama | gemma3:27b | — | 0 | 0 |
| ollama | gemma3:12b | — | 0 | 0 |
| ollama | qwq | — | 0 | 0 |
| ollama | deepseek-r1 | — | 0 | 0 |
| ollama | mistral-small3.1 | — | 0 | 0 |
| ollama | llama3.3 | — | 0 | 0 |
| ollama | phi4 | — | 0 | 0 |
| openrouter | google/gemini-2.0-flash-001 | — | 0.1 | 0.4 |
| openrouter | google/gemini-2.5-pro-exp-03-25 | — | 0 | 0 |
| openrouter | deepseek/deepseek-chat-v3-0324:free | — | 0 | 0 |
| openrouter | deepseek/deepseek-r1:free | — | 0 | 0 |
| openrouter | microsoft/mai-ds-r1:free | — | 0 | 0 |
| openrouter | google/gemini-2.5-pro-preview-03-25 | — | 1.25 | 10 |
| openrouter | openai/o3 | — | 10 | 40 |
| openrouter | openai/o4-mini | 0.45 | 1.1 | 4.4 |
| openrouter | openai/o4-mini-high | — | 1.1 | 4.4 |
| openrouter | openai/o1-pro | — | 150 | 600 |
| openrouter | meta-llama/llama-3.3-70b-instruct | — | 120 | 600 |
| openrouter | google/gemma-3-12b-it:free | — | 0 | 0 |
| openrouter | google/gemma-3-12b-it | — | 50 | 100 |
| openrouter | google/gemma-3-27b-it:free | — | 0 | 0 |
| openrouter | google/gemma-3-27b-it | — | 100 | 200 |
| openrouter | qwen/qwq-32b:free | — | 0 | 0 |
| openrouter | qwen/qwq-32b | — | 150 | 200 |
| openrouter | qwen/qwen-max | — | 1.6 | 6.4 |
| openrouter | qwen/qwen-turbo | — | 0.05 | 0.2 |
| openrouter | mistralai/mistral-small-3.1-24b-instruct:free | — | 0 | 0 |
| openrouter | mistralai/mistral-small-3.1-24b-instruct | — | 0.1 | 0.3 |
| openrouter | thudm/glm-4-32b:free | — | 0 | 0 |

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docs/scripts/models-json-to-markdown.js Normal file
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import fs from 'fs';
import path from 'path';
import { fileURLToPath } from 'url';
const __filename = fileURLToPath(import.meta.url);
const __dirname = path.dirname(__filename);
const supportedModelsPath = path.join(
__dirname,
'..',
'modules',
'supported-models.json'
);
const outputMarkdownPath = path.join(
__dirname,
'..',
'..',
'docs',
'models.md'
);
function formatCost(cost) {
if (cost === null || cost === undefined) {
return '—';
}
return cost;
}
function formatSweScore(score) {
if (score === null || score === undefined || score === 0) {
return '—';
}
return score.toString();
}
function generateMarkdownTable(title, models) {
if (!models || models.length === 0) {
return `## ${title}\n\nNo models in this category.\n\n`;
}
let table = `## ${title}\n\n`;
table += '| Provider | Model Name | SWE Score | Input Cost | Output Cost |\n';
table += '|---|---|---|---|---|\n';
models.forEach((model) => {
table += `| ${model.provider} | ${model.modelName} | ${formatSweScore(model.sweScore)} | ${formatCost(model.inputCost)} | ${formatCost(model.outputCost)} |\n`;
});
table += '\n';
return table;
}
function main() {
try {
const correctSupportedModelsPath = path.join(
__dirname,
'..',
'..',
'scripts',
'modules',
'supported-models.json'
);
const correctOutputMarkdownPath = path.join(__dirname, '..', 'models.md');
const supportedModelsContent = fs.readFileSync(
correctSupportedModelsPath,
'utf8'
);
const supportedModels = JSON.parse(supportedModelsContent);
const mainModels = [];
const researchModels = [];
const fallbackModels = [];
for (const provider in supportedModels) {
if (Object.hasOwnProperty.call(supportedModels, provider)) {
const models = supportedModels[provider];
models.forEach((model) => {
const modelEntry = {
provider: provider,
modelName: model.id,
sweScore: model.swe_score,
inputCost: model.cost_per_1m_tokens
? model.cost_per_1m_tokens.input
: null,
outputCost: model.cost_per_1m_tokens
? model.cost_per_1m_tokens.output
: null
};
if (model.allowed_roles.includes('main')) {
mainModels.push(modelEntry);
}
if (model.allowed_roles.includes('research')) {
researchModels.push(modelEntry);
}
if (model.allowed_roles.includes('fallback')) {
fallbackModels.push(modelEntry);
}
});
}
}
const date = new Date();
const monthNames = [
'January',
'February',
'March',
'April',
'May',
'June',
'July',
'August',
'September',
'October',
'November',
'December'
];
const formattedDate = `${monthNames[date.getMonth()]} ${date.getDate()}, ${date.getFullYear()}`;
let markdownContent = `# Available Models as of ${formattedDate}\n\n`;
markdownContent += generateMarkdownTable('Main Models', mainModels);
markdownContent += generateMarkdownTable('Research Models', researchModels);
markdownContent += generateMarkdownTable('Fallback Models', fallbackModels);
fs.writeFileSync(correctOutputMarkdownPath, markdownContent, 'utf8');
console.log(`Successfully updated ${correctOutputMarkdownPath}`);
} catch (error) {
console.error('Error transforming models.json to models.md:', error);
process.exit(1);
}
}
main();