selftune-dev/selftune

Skill observability & self-improving toolkit for agent skills.

This repository also configures its own agents. See what selftune tells them →

18Stars on the repository
8Mods indexed here, across every type
1mo agoLast push, which is what freshness is scored on
MITLicence, which decides whether bodies are shown

diagnosis-analyst

01

selftune-dev/selftune

Agent Claude Code

Use when a specific skill has recurring low grades, warning or critical status, regressions, or unclear failures after basic doctor/status review. Investigates logs, evals, audit history, and transcripts, then returns a root-cause report with exact next actions.

not rated 18 1mo ago A 58 tokens original MIT

selftune-dev/selftune

Agent Claude Code

Produces one bounded, review-only SKILL.md body proposal from an already-selected local evidence cohort.

not rated 18 1mo ago A 26 tokens original MIT

evolution-reviewer

03

selftune-dev/selftune

Agent Claude Code

Use when reviewing a dry-run or pending evolution proposal before deployment, especially for high-stakes skills, marginal improvements, or recent regressions. Compares old vs new content, checks evidence quality, and returns an approve or reject verdict with conditions.

not rated 18 1mo ago A 54 tokens original MIT

integration-guide

04

selftune-dev/selftune

Agent Claude Code

Use when setting up selftune in a complex repo: monorepo, multi-skill workspace, mixed agent platforms, unclear hook state, or install problems that basic init/doctor does not resolve. Detects project structure, validates configuration, and returns or applies a verified setup plan.

not rated 18 1mo ago A 0 tokens original MIT

pattern-analyst

05

selftune-dev/selftune

Agent Claude Code

Use when multiple skills may overlap, misroute, or interfere with each other, or when composability results suggest moderate or severe conflict. Analyzes trigger ownership, query overlap, and cross-skill health, then returns a conflict matrix and routing recommendations.

not rated 18 1mo ago A 56 tokens original MIT

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