القائمة
Run self-evolution cycle — score agents, detect drift, propose instruction improvements. Use at session end, weekly cadence, or monthly deep review.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Hard-learned development rules by domain — Python, FastAPI, React, Testing. Prevents the specific mistakes that caused 70+ audit findings across v0.21.0-v0.21.3.
Mandatory pre-merge quality checks for production code — security scan, packaging test, API consistency, no silent failures. Prevents the issues that caused 4 emergency releases in v0.21.x.
Pre-release validation — packaging verification, user acceptance testing, security scan, API drift detection. Prevents the recurring pattern of shipping broken wheels and missing files.
Test the library from an end-user perspective — pip install, import, run all workflows. Catches packaging, import, and API issues that internal tests miss.
Discover exact API function signatures, parameter names, and types from structural_lib. Use BEFORE wrapping or calling any API function. Prevents the #1 agent mistake: guessing parameter names (b_mm not width, fck not concrete_grade).
Run a structured innovation research cycle — discover gaps, propose novel capabilities, prototype and validate breakthrough ideas for structural engineering.
| name | agent-evolution |
| description | Run self-evolution cycle — score agents, detect drift, propose instruction improvements. Use at session end, weekly cadence, or monthly deep review. |
Run the self-evolving agent improvement cycle — from data collection through scoring, drift detection, and instruction evolution.
./run.sh evolve --status
./run.sh feedback log --agent <name>
Run these 5 steps in order:
Collect session data:
.venv/bin/python scripts/agent_session_collector.py
Score agents:
.venv/bin/python scripts/agent_scorer.py --all
Detect drift:
.venv/bin/python scripts/agent_drift_detector.py
Check compliance:
.venv/bin/python scripts/agent_compliance_checker.py
Analyze trends:
.venv/bin/python scripts/agent_trends.py --weekly
Or one command: ./run.sh evolve --review weekly
Additional steps beyond the weekly cycle:
Run weekly cycle first (steps 1-5 above)
Export paper data:
.venv/bin/python scripts/export_paper_data.py
Propose evolutions:
.venv/bin/python scripts/agent_evolve_instructions.py --propose
Review proposals:
.venv/bin/python scripts/agent_evolve_instructions.py --list
Apply approved:
.venv/bin/python scripts/agent_evolve_instructions.py --apply --confirm
Or: ./run.sh evolve --review monthly
Emergency rollback procedure:
.venv/bin/python scripts/agent_evolve_instructions.py --rollback <agent-name>
| File | Purpose |
|---|---|
logs/agent-performance/scorecard_index.json | Latest scores per agent |
logs/agent-performance/evolution-log.json | Applied evolution history |
logs/agent-performance/pending-evolutions.json | Proposed changes |
logs/agent-performance/sessions/*.json | Raw session data |
logs/agent-performance/trends/*.json | Trend analyses |
logs/agent-performance/backups/*.bak | Agent file backups |
--dry-run or --propose before --apply--rollbackThe system requires 15-20 sessions of data collection before evolution proposals become meaningful. During burn-in, focus on OBSERVE and MEASURE only — do not EVOLVE.