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Run system self-evolution cycle (SEAI framework). Use when user asks for self-evolution, system improvement, SEAI cycle, /evolve, or to analyze evolution history.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Use when you need to generate or enhance user interface and user experience designs.
Manage Things 3 via the `things` CLI on macOS (add/update projects+todos via URL scheme; read/search/list from the local Things database). Use when a user asks Clawdbot to add a task to Things, list inbox/today/upcoming, search tasks, or inspect projects/areas/tags.
Collaborative thinking partner for exploring complex problems through questioning
Use when you need to access and apply superpowers within your Claude projects.
A universal self-improving agent that learns from ALL skill experiences. Uses multi-memory architecture (semantic + episodic + working) to continuously evolve the codebase. Auto-triggers on skill completion/error with hooks-based self-correction.
Use when you need to analyze your own reasoning process to improve accuracy.
| name | evolve |
| description | Run system self-evolution cycle (SEAI framework). Use when user asks for self-evolution, system improvement, SEAI cycle, /evolve, or to analyze evolution history. |
7-phase SEAI cycle: Analyze → Reflect → Generate improvements → Learn → Adapt → Evaluate → Plan next. Feeds into the gene pool: successful strategies become reusable genes for future cycles.
# Single evolution cycle (safe mode — asks before applying)
python3 _scripts/self_evolution.py cycle --safe
# Multiple continuous cycles
python3 _scripts/self_evolution.py continuous --iterations 3 --safe
# View evolution history and trends
python3 _scripts/self_evolution.py analyze --iterations 5 --report
/reflect → observe system behavior (self_reflection.py)
/evolve → generate system improvements (self_evolution.py) ← here
/insights → manage insight lifecycle (insight_enhancement.py)
/skill-evolve → score + improve skills + genes (skill_evolution.py)
/gene → view and apply proven genes
_logs/evolution_log.json — full iteration history with phases, improvements, and metrics