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Documentation Index

Fetch the complete documentation index at: https://docs.selftune.dev/llms.txt

Use this file to discover all available pages before exploring further.

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The open standard

Agent Skills is an open format for giving AI agents new capabilities. It defines how skills are structured, discovered, and activated across compatible clients. selftune builds on this standard. Every skill that follows the agent skills spec works with selftune — and selftune makes those skills better by adding observability, grading, and evolution.

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Compatible agents

Skills built to the spec work across all compatible agents. selftune does not offer the same depth on every runtime, so the practical support matrix is:
PlatformSession captureLLM-backed judge and evolveRuntime replay validationNotes
Claude CodeFull hooks + ingestYesYesPrimary platform with the deepest integration
OpenAI CodexHooks, wrapper, and ingestYesExperimentalOptimizer agents are inlined into codex exec
OpenCodePlugin hooks + ingestYesExperimentalNo prompt-submit hook event and no hard-blocking guards
PiExtension hooks + ingestYesNoselftune uses pi -p and inlines optimizer instructions because Pi has no native subagent flag
OpenClawIngest + cronNoNoExperimental; no real-time hooks
ClinePartial hooksNoNoExperimental; post-tool and task lifecycle coverage only
The full list of spec-compatible agents is maintained at agentskills.io, including Cursor, GitHub Copilot, Gemini CLI, VS Code, and more.

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Where to find skills

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skills.sh

skills.sh is the community registry for agent skills. Browse, search, and install skills: 
npx skills add skill-name

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Anthropic’s example skills

The anthropics/skills repository contains reference implementations and examples from the team that created the spec.

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GitHub

Any GitHub repo with a valid SKILL.md can be installed directly: 
npx skills add github-username/repo-name

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selftune registry

The selftune registry adds contributor signal data on top of the skill — trigger pass rates, evolution history, and contributor insights: 
# Push a team skill to the registry
selftune registry push csv-analysis

# Install a skill
npx skills add selftune-dev/selftune

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How selftune extends the spec

The agent skills spec defines how skills are structured and discovered. selftune adds what happens after discovery:
Agent skills specselftune adds
Skill structure (SKILL.md, scripts, references)Observability (session capture, grading)
Progressive disclosure (3-tier loading)Evolution (automatic description improvement)
Description-based triggeringTrigger accuracy measurement
Compatible client listCross-platform session ingestion
Manual skill authoringContinuous improvement from real usage
Think of it as the difference between writing a skill and operating a skill.

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Key resources

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Specification and reference

Agent Skills Spec

The complete open standard — structure, discovery, activation, scripts, and client implementation.

Spec GitHub Repo

Source for the spec, reference library, and validation tools.

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Skills and examples

skills.sh

Community skill registry. Browse, search, and install skills.

Anthropic Example Skills

Reference implementations from the creators of the spec.

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selftune

selftune GitHub

Open-source CLI and skill. MIT licensed.

selftune Cloud

Team dashboards, contributor signals, and the skill registry.

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Community

Agent Skills Discord

The official community for the agent skills spec.

selftune Discussions

Ask questions, share skills, and discuss evolution strategies.

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Validation tools

The spec provides a reference library for validating skills: 
# Validate a skill against the spec
npx skills-ref validate ./my-skill
This checks:
  • Frontmatter fields (name format, description length, required fields)
  • Directory structure
  • Name-directory match
  • Description quality

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Next steps

Quickstart

Install selftune and see your first skill health report.

Writing Descriptions

Write descriptions that trigger reliably across all compatible agents.

Publishing Skills

Package and share your skills with the community.

Structuring Skills

Organize skills that scale beyond simple use cases.