skill-improver

To identify skill improvement opportunities without user feedback, use passive session signal analysis to detect friction, abandonment, and flow issues. This logs passive observation data to automatically surface concrete proposals for skill quality elevation.

Continuous improvement for skill library health works by observing session flows to surface structured improvement proposals. It analyzes passive signals to generate actionable updates for public SKILL.md files and private maturity tracking, enabling library evolution.

To generate actionable proposals from session abandonment signals, activate passive observation across your skill sessions. It analyzes friction and flow data to automatically produce sanitized proposals for public SKILL.md updates and private maturity tracking.

Yes, passive skill signal analysis stores insights privately. It requires no user prompts and produces only sanitized proposals for public SKILL.md updates, while maintaining private maturity tracking for internal library health.

Yes, you can use maturity tracking to manage private-to-public skill promotion and demotion workflows. It leverages data from passive session signals to orchestrate skill maturity and library health evolution.