Agent Skills is a public, open-source repository on GitHub that centralizes the development, curation, and collaboration around AI agent skills. In an era where agent behavior depends on a growing set of capabilities, this project provides a single, version-controlled space where researchers, engineers, and product teams can contribute, review, and iterate on skills with provenance and accountability. By bringing together a diverse community under a public repository, it accelerates experimentation, reproducibility, and cross-team collaboration in agent development.
Core Value Proposition
Agent Skills offers a centralized library and collaboration workflow for agent skills, built on open source principles. Hosted on GitHub, it leverages familiar Git workflows—forks, branches, pull requests, and issue tracking—to manage contributions, document decisions, and track the evolution of each skill. The result is a transparent, reusable, and auditable foundation that reduces duplication, speeds up iteration, and strengthens the rigor of AI agent research and deployment.
Key Features
- Open source collaboration: Leverage a global community to contribute, review, and refine agent skills. All changes are tracked in a transparent, auditable history, enabling reproducibility and peer feedback.
- Public agent skills library: A centralized, browsable catalog of skills, components, and patterns that teams can reuse and extend, lowering onboarding friction and accelerating prototyping.
- Version-controlled development: Every alteration lives in Git with PRs, issues, and branches, so provenance and reproducibility are preserved across experiments and deployments.
- Community-driven contributions: Invite researchers and developers from academia and industry to shape standards, contribute improvements, and participate in governance through discussions and issues.
- Git-based collaboration workflow: Familiar GitHub workflows enable forks, pull requests, CI checks, and code reviews, improving quality while keeping contribution approachable.
- Rich docs and examples: Comprehensive documentation and example notebooks help users understand how to use, extend, and verify each skill in real workflows.
- Easy fork and PRs: Anyone can fork the repository, implement enhancements, and submit pull requests, fostering inclusivity and speed.
- AI research friendly: Structured for experiments, benchmarking, and reproducibility, making it easier to share results and validate agent behavior across teams.
Who Is This For?
- Researchers and data scientists prototyping new agent skills who want a shared space to publish, critique, and compare approaches.
- Product teams integrating agent capabilities into applications, seeking reusable skills and clear provenance for deployments.
- Open-source developers and contributors looking to influence the direction of agent skill standards and tooling.
- Tooling engineers building evaluation pipelines, dashboards, or CI tests that rely on a common set of agent skills and benchmarks.
Use Cases
- A research lab publishes a new navigation skill and invites peer review, accelerating validation through community feedback and shared datasets.
- An AI-powered app team reuses existing skills from the catalog, forks them for customization, and submits improvements via PRs that are reviewed by the community.
- An external contributor submits a new dialogue management pattern, providing documentation, tests, and benchmarks to demonstrate improvements.
- A CI-driven workflow integrates agent-skill testing into continuous integration, enabling automated evaluation when new skills are added or updated.
Under the Hood
- Public, GitHub-hosted repository enabling classic open-source collaboration flows (forks, PRs, issues) with transparent governance.
- Version control across all skills, including provenance trails for every change and discussion.
- Documentation-rich, with examples and notebooks to facilitate learning, experimentation, and onboarding.
- Interoperability with common ML tooling and datasets to support reproducible experiments and benchmarking.
- Security-aware practices and community guidelines to ensure responsible collaboration and quality control.
Get Started
- Visit https://github.com/anthropics/skills to explore the repository and the catalog of skills.
- Review contribution guidelines, licensing notes, and example workflows.
- Fork the project, implement or modify a skill, and submit a pull request for peer review.
- Engage in discussions via issues to shape standards, governance, and future directions.
Closing
Join the community to accelerate agent skills development through transparent, collaborative, and reproducible workflows.
