Self-Learning Skills

Automatically improve skills based on execution outcomes. When a skill fails repeatedly, Zeph uses self-reflection and LLM-generated improvements to create better skill versions.

Configuration

[skills.learning]
enabled = true
auto_activate = false     # require manual approval for new versions
min_failures = 3          # failures before triggering improvement
improve_threshold = 0.7   # success rate below which improvement starts
rollback_threshold = 0.5  # auto-rollback when success rate drops below this
min_evaluations = 5       # minimum evaluations before rollback decision
max_versions = 10         # max auto-generated versions per skill
cooldown_minutes = 60     # cooldown between improvements for same skill

How It Works

1. Each skill invocation is tracked as success or failure
2. When a skill’s success rate drops below improve_threshold, Zeph triggers self-reflection
3. The agent retries with adjusted context (1 retry per message)
4. If failures persist beyond min_failures, the LLM generates an improved skill version
5. New versions can be auto-activated or held for manual approval
6. If an activated version performs worse than rollback_threshold, automatic rollback occurs

Chat Commands

Set auto_activate = false (default) to review and manually approve LLM-generated skill improvements before they go live.

Skill versions and outcomes are stored in SQLite (skill_versions and skill_outcomes tables).