I built a skill (/skill-opt) to automate the entire evaluation, reflection, and patch deployment cycle through an interactive, natural language conversation with your agent.
Features
- Generates a self-contained Python optimizer on the fly using standard libraries (no pip install or external repo needed).
- Probes recent session transcripts to turn real developer corrections into regression benchmarks.
- Optimize a single file or point it at an entire folder of skills to tune them all in sequence.
- Can run on a recurring schedule to continuously optimize skills against recent real-life agent runs.
- Only commits patches with measured score gains on held-out tasks.
- Runs across Gemini, Claude, OpenAI, or OpenRouter with live progress updates in chat.
- Saves timestamped backups before modifying source files.
LMKWYT!
I built a skill (/skill-opt) to automate the entire evaluation, reflection, and patch deployment cycle through an interactive, natural language conversation with your agent.
Features
LMKWYT!