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Add a new MCP tool that bridges the gap between fully automatic evolution (inside execute_task) and manual repair (fix_skill). scan_evolution_opportunities lets host agents proactively inspect which skills could benefit from evolution by: 1. Loading execution analyses marked as evolution candidates 2. Enriching each with SkillRecord usage statistics (completion rate, fallback rate, effective rate) 3. Returning a structured JSON report with prioritized suggestions This enables an "agent-in-the-loop" evolution pattern for all host agents (Claude Code, Codex, nanobot, Cursor, etc.): periodic scan, review report, selectively apply fixes. Closes #24 Made-with: Cursor |
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| .. | ||
| agents | ||
| cloud | ||
| communication | ||
| config | ||
| grounding | ||
| host_detection | ||
| host_skills | ||
| llm | ||
| local_server | ||
| platforms | ||
| prompts | ||
| recording | ||
| skill_engine | ||
| skills | ||
| utils | ||
| .env.example | ||
| __init__.py | ||
| __main__.py | ||
| dashboard_server.py | ||
| mcp_server.py | ||
| tool_layer.py | ||