capability-evolver
SolidSelf-evolution workflow for the agent. Before substantive work, recall past outcomes from evolution memory; while editing, detect improvement signals; at task end, record the outcome; when reusable, distill or search the EvoMap network for proven genes/capsules. Use when the user starts non-trivial work (a feature, a fix, a refactor) or asks the agent to "evolve", "learn from this", or "remember how this went".
Install
Quality Score: 91/100
Skill Content
Details
- Author
- Dianel555
- Repository
- Dianel555/DSkills
- Created
- 6 months ago
- Last Updated
- today
- Language
- Python
- License
- MIT
Integrates with
Bundled in these plugins
Similar Skills
Semantically similar based on skill content — not just same category
evolve
Analyzes agent/skill failures, drafts prompt/permission fixes. Triggers: improve agent, refine skill, system prompt, optimize agent.
self-evolution
Self-healing and self-evolving pattern for agents operating against repo capabilities, scripts, skills, sub-agents, selectors, workflows, and external systems. Classifies evolution events into four tiers — Friction/Workaround, Gap, Failure, Regression — applies repo-profile-gated edits with appropriate autonomy, verifies the fix, and updates domain reference files ("The Map, not the Diary"). Invoke whenever a tool call, subprocess, or workflow returns a failure OR whenever the agent used a workaround, bypass, guess, or manual substitute for an existing repo capability.
evo
Use this skill when the user identifies a behavior to improve, a mistake to prevent, a project convention, a team role, a tech-stack constraint, or any pattern worth persisting beyond the current session. Captures a lesson and adds it to the appropriate evolution overlay — a per-agent file, per-skill file, or project-wide rules file. Appends to `.ievo/evolution/<scope>/<name>.md` (overlay file). The agent/skill body is never modified — overlays are read at dispatch time via a one-time marker injection.