chore: task management some more

.taskmaster/tasks/task_104.txt

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+# Task ID: 104
+# Title: Implement 'scope-up' and 'scope-down' CLI Commands for Dynamic Task Complexity Adjustment
+# Status: pending
+# Dependencies: 3, 11, 19, 94
+# Priority: high
+# Description: Add new CLI commands 'scope-up' and 'scope-down' to enable users to dynamically increase or decrease the complexity of tasks or subtasks, with support for multiple IDs, strength levels, and milestone-aware adjustments.
+# Details:
+1. Extend the CLI (commands.js) to introduce 'scope-up' and 'scope-down' commands, following established subcommand patterns for consistency and discoverability. 
+2. Accept comma-separated task/subtask IDs and an optional '--strength' flag (light|regular|heavy, defaulting to regular). Validate all inputs, ensuring referenced tasks/subtasks exist and strength is valid.
+3. Fetch current task details and associated milestone context to inform the adjustment logic.
+4. Implement core logic functions that:
+   - Construct context-aware AI prompts for scaling complexity up or down, leveraging the current state, project phase, and strength parameter.
+   - Call the unified AI service (ai-services-unified.js) to generate new task/subtask content at the desired complexity level.
+   - Replace existing task details and subtasks with the AI-generated output, preserving historical versions for rollback/comparison.
+   - Ensure task dependency integrity and update tasks.json and related files accordingly.
+5. Integrate robust error handling for invalid IDs, parameters, or AI failures, and provide clear CLI output showing before/after differences.
+6. Add corresponding MCP tool equivalents for integrated environments and update documentation/help text to reflect new commands and usage patterns.
+7. Ensure compatibility with batch operations, milestone-based guidelines, and existing task management workflows.
+
+# Test Strategy:
+- Write unit and integration tests for both 'scope-up' and 'scope-down' commands, covering single and multiple ID scenarios, all strength levels, and edge cases (e.g., non-existent IDs, invalid strength values).
+- Simulate CLI usage to verify correct parsing, validation, and error handling.
+- Test AI prompt construction and output integration, ensuring that task complexity is adjusted as expected for each strength level and milestone context.
+- Verify that historical data is preserved and that before/after summaries are accurate and clear.
+- Confirm that task dependencies remain intact and that batch operations work as intended.
+- Validate MCP tool integration and documentation updates.