Understand skill health

Skill health is a summary of the evidence SelfTune has observed. It is not a permanent grade and it is not meaningful without enough representative usage.

Ask your agent

Use SelfTune to explain the health of my installed skills. Separate observed
problems from no-data states, identify the evidence behind each conclusion, and
recommend at most one next action per skill. Do not modify any skill.

Inspect health manually

selftune sync
selftune status

Or open the local dashboard:

selftune dashboard

State	Meaning	Reasonable next action
Healthy	Current evidence meets the accepted checks	Keep observing
Warning	Evidence suggests drift or a bounded problem	Inspect the cited sessions or evals
Critical	A current check failed materially	Pause automatic changes and diagnose
Unknown / no data	Evidence is absent or insufficient	Use the skill naturally or add a representative eval

Read the evidence, not only the label

Check the observation count, time window, skill version, harness, and kind of evidence. A high score from a tiny or synthetic-only sample may be less useful than a lower score from representative work. A no-data state is honest and should not be converted into a failure.

Success criteria

You should be able to answer:

Which skill needs attention now?
What evidence supports that conclusion?
Is the issue activation, execution, output, or insufficient data?
What is the smallest safe next action?

Start here

Use SelfTune

Run it your way

Concepts

Reference

Understand skill health

Ask your agent

Inspect health manually

Read the evidence, not only the label

Success criteria

​Ask your agent

​Inspect health manually

​Read the evidence, not only the label

​Success criteria

Ask your agent

Inspect health manually

Read the evidence, not only the label

Success criteria