clawd
d81e403f01
COMPLETED TASKS: ✅ 06-01: Workout Swap System - Added swapped_from_id to workout_logs - Created workout_swaps table for history - POST /api/workouts/:id/swap endpoint - GET /api/workouts/available endpoint - Reversible swaps with audit trail ✅ 06-02: Muscle Group Recovery Tracking - Created muscle_group_recovery table - Implemented calculateRecoveryScore() function - GET /api/recovery/muscle-groups endpoint - GET /api/recovery/most-recovered endpoint - Auto-tracking on workout log completion ✅ 06-03: Smart Workout Recommendations - GET /api/recommendations/smart-workout endpoint - 7-day workout analysis algorithm - Recovery-based filtering (>30% threshold) - Top 3 recommendations with context - Context-aware reasoning messages DATABASE CHANGES: - Added 4 new tables: muscle_group_recovery, workout_swaps, custom_workouts, custom_workout_exercises - Extended workout_logs with: swapped_from_id, source_type, custom_workout_id, custom_workout_exercise_id - Created 7 new indexes for performance IMPLEMENTATION: - Recovery service with 4 core functions - 2 new route handlers (recovery, smartRecommendations) - Updated workouts router with swap endpoints - Integrated recovery tracking into POST /api/logs - Full error handling and logging TESTING: - Test file created: /backend/test/phase-06-tests.js - Ready for E2E and staging validation STATUS: Ready for frontend integration and production review Branch: feature/06-phase-06
62 lines
1.5 KiB
Markdown
62 lines
1.5 KiB
Markdown
# Automatic Topology Selection
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## Purpose
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Automatically select the optimal swarm topology based on task complexity analysis.
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## How It Works
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### 1. Task Analysis
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The system analyzes your task description to determine:
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- Complexity level (simple/medium/complex)
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- Required agent types
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- Estimated duration
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- Resource requirements
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### 2. Topology Selection
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Based on analysis, it selects:
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- **Star**: For simple, centralized tasks
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- **Mesh**: For medium complexity with flexibility needs
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- **Hierarchical**: For complex tasks requiring structure
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- **Ring**: For sequential processing workflows
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### 3. Example Usage
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**Simple Task:**
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```
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Tool: mcp__claude-flow__task_orchestrate
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Parameters: {"task": "Fix typo in README.md"}
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Result: Automatically uses star topology with single agent
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```
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**Complex Task:**
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```
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Tool: mcp__claude-flow__task_orchestrate
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Parameters: {"task": "Refactor authentication system with JWT, add tests, update documentation"}
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Result: Automatically uses hierarchical topology with architect, coder, and tester agents
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```
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## Benefits
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- 🎯 Optimal performance for each task type
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- 🤖 Automatic agent assignment
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- ⚡ Reduced setup time
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- 📊 Better resource utilization
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## Hook Configuration
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The pre-task hook automatically handles topology selection:
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```json
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{
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"command": "npx claude-flow hook pre-task --optimize-topology"
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}
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```
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## Direct Optimization
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```
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Tool: mcp__claude-flow__topology_optimize
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Parameters: {"swarmId": "current"}
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```
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## CLI Usage
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```bash
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# Auto-optimize topology via CLI
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npx claude-flow optimize topology
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``` |