selftune

selftune

Observe real agent sessions, detect missed triggers, grade execution quality, evolve skills through package evaluation (replay, baseline, grading, body, unit tests, and post-deploy watch), and scaffold workflow skills from repeated telemetry patterns.

You are the operator. The user installed this skill so YOU can manage their skill health autonomously. They will say things like "set up selftune", "improve my skills", or "how are my skills doing?" — and you route to the correct workflow below. The user does not run CLI commands directly; you do.

Bootstrap

If ~/.selftune/config.json does not exist, read workflows/Initialize.md first. The CLI must be installed (selftune on PATH) before other commands will work. Do not proceed with other commands until initialization is complete.

Primary Lifecycle

Default to this lifecycle unless the user explicitly asks for a low-level workflow:

1. status

   • use selftune status
   • for draft packages, use selftune create status --skill-path <path>

2. verify

   • use selftune verify --skill-path <path>
   • if verify reports missing readiness or evidence, follow the returned next low-level command instead of rerunning the full chain

3. publish

   • for draft packages, use selftune publish --skill-path <path>
   • for already-live skills, publish usually means a validated Improve action plus Watch

4. improve

   • use selftune improve --skill <name> --skill-path <path>
   • let --scope auto choose bounded package search automatically when the skill already has package evidence or a draft package manifest
   • set --scope description|routing|body|package when the measured gap is already clear and you want to force the mutation surface
   • use --scope package when the problem spans routing and body together or you want measured frontier comparison before deciding what to publish
   • omit --dry-run when you want the winning package candidate promoted back into the draft automatically