skill-feedback
SolidCapture and aggregate real-world usage feedback for Agent Skills so the Skill Quality Gate loop can keep improving them over time. Use it whenever a skill misfires or underperforms: a skill triggered wrongly (wrong trigger), failed to auto-load on a relevant request (near-miss / description gap), produced a wrong, broken, or low-quality output (output issue), or the user manually corrected its result (manual correction). Also use it to review accumulated skill feedback before running skill-forge, or to close the feedback loop that raises skill quality. Writes one structured JSON object per line to feedback/<skill>/YYYY-MM-DD.jsonl and can summarize them into a report/export that feeds skill-forge's Optimize-description step. Trigger phrases: 'skill feedback', 'log skill feedback', 'skill triggered wrongly', 'near-miss trigger', 'wrong trigger', 'output issue', 'manual correction', 'improve skill', 'skill quality', 'feedback loop'.
Install
Quality Score: 83/100
Skill Content
Details
- Author
- bestdeejay-design
- Repository
- bestdeejay-design/agent-skills
- Created
- 1 months ago
- Last Updated
- today
- Language
- Python
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
skill-from-feedback
Use when the user wants to modify, improve, patch, or revise an existing agent skill from feedback — real session failures, “this skill did X wrong”, tighten triggers, fix workflow holes, or turn review notes into SKILL.md changes. Not for creating a brand-new skill from scratch (use capture-workflow / create-skill) and not for scanning all sessions (use agent-session-auditor).
skill-feedback
Review recent Claude Code sessions that used a specific agent or skill and submit per-session feedback as GitHub issues. Use when the user says "submit [agent/skill] feedback", "review my [agent/skill] sessions", or "file [agent/skill] feedback issues".
skill-evolve
A meta-skill that takes feedback after a skill runs and automatically improves the corresponding SKILL.md. Use when a skill was wrong or incomplete, or to record a newly discovered gotcha.