Loading...
Loading...
Found 7 Skills
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.
Self-report agent issues by logging user corrections for later review, then resume with the correct skill. Use when a user says "don’t do that", "stop doing X", "always do Y", or requests self-correction.
Implement Corrective RAG (CRAG) with retrieval validation, fallback strategies, and self-correction. Use this skill when RAG outputs need quality guarantees and automatic error correction. Activate when: CRAG, corrective RAG, retrieval validation, fallback search, self-correcting RAG, grounded generation.
Use when a Scenario output must be checked and improved rather than accepted first roll: iterating a generation until it matches the brief, fixing a batch that came back off-brief, retrying failed shots methodically, wiring an automated generate, review, revise loop, or deciding whether to re-prompt, swap references, inpaint, post-process, or change model. Keywords: refine, iterate, critique, review loop, QA, self-correction, verify, acceptance criteria, retry, drift.
Battle-tested Claude Code workflows from power users. Self-correcting memory, parallel worktrees, wrap-up rituals, and the 80/20 AI coding ratio. Distilled from real production use.
Use when the workflow needs to self-correct, improve over time, or establish feedback loops and evaluation cycles.
Analyze and correct previous responses when questioned or when contradictions are detected. Use this skill when the user challenges your reasoning, points out inconsistencies, or asks 'what makes you think that?' to help you review your logic, identify errors in your previous statements, and provide accurate corrections. Useful for maintaining consistency, admitting mistakes, and rebuilding trust through transparent self-evaluation.