openai/skillsPublic

Skills Catalog for Codex

AI summary: A deprecated historical repository of skill definitions and tool patterns for OpenAI's early Codex platform.

Stars
27.9K
+40 today
Forks
1.9K
Watchers
160
Open issues
87
Open PRs
0
Contributors
~35
Commits
114
Branches
20

PythonNo licenseCreated Nov 25, 2025Last push 25d ago+252 stars this week+2.5K this month

Quick answers

What is skills?
A deprecated historical repository of skill definitions and tool patterns for OpenAI's early Codex platform.
What does skills do?
Agent Skills is an archived, deprecated repository previously used by OpenAI to distribute capability packages for their early Codex models. It defined a standardized structure for folders containing instructions, scripts, and resources that allowed AI agents to discover and use specific tools. The repository cataloged both curated and experimental skills, demonstrating an early approach to modular agent tool integration before modern function calling APIs existed. While it has been replaced by the modern OpenAI Plugins ecosystem, it serves as a historical reference for structuring agentic tools. It highlights the evolution of how language models interface with external systems.
Who is skills for?
AI researchers and developers looking for historical examples of modular agent capabilities, or those maintaining legacy Codex systems. No active development is recommended.
How do I get started with skills?
Review the repository structure for historical reference.
How popular is skills on GitHub?
openai/skills has 27,852 stars and 1,894 forks on GitHub, and gained 252 stars in the last 7 days.

Star history

since Jul 29, 2026
010K20KJul 2026Aug 2026Sep 2026Oct 2026
27.9K stars as of Oct 3, 2026. Measured daily since Jul 29, 2026; GitHub no longer exposes earlier star timestamps.

Contribution activity

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114 commits in the last yearLessMore

Signals and awards

derived from tracked data
  • Widely adopted

    27,852 stars

  • Continuous integration

    Automated checks passing

  • Repeat trending

    21 trending appearances

What skills does

Agent Skills is an archived, deprecated repository previously used by OpenAI to distribute capability packages for their early Codex models. It defined a standardized structure for folders containing instructions, scripts, and resources that allowed AI agents to discover and use specific tools. The repository cataloged both curated and experimental skills, demonstrating an early approach to modular agent tool integration before modern function calling APIs existed. While it has been replaced by the modern OpenAI Plugins ecosystem, it serves as a historical reference for structuring agentic tools. It highlights the evolution of how language models interface with external systems.

AI researchers and developers looking for historical examples of modular agent capabilities, or those maintaining legacy Codex systems. No active development is recommended.

  • Modular Skill Packages: Structured as standalone folders containing all necessary instructions and resources for a specific AI task.
  • Curated Tool Tracks: Categorized skills to separate stable, trusted tools from experimental or community-driven integrations.
  • Native Codex Integration: Designed to be easily installed and executed natively by early versions of OpenAI's Codex.
  • Open Standard Demonstration: Highlighted the early Agent Skills open standard for modular AI tool development and prompt design.
  • Historical Archive: Now serves primarily as a deprecated archive, redirecting users to the modern OpenAI Plugins repository.

Where teams use it

Historical Reference

Researchers study the repository to understand the early evolution and directory structure of modular tools for coding agents.

Legacy System Support

Developers maintaining older, isolated Codex integrations can still reference the experimental skills provided in the archive.

Skill Structure Analysis

Engineers examine the existing folders to understand baseline best practices for writing prompt instructions for AI tools.

Standard Review

Architects review the implementation details of the original open standard to inform modern plugin system designs.

Getting started: Review the repository structure for historical reference.

README

main branch

Important

This repository is deprecated. For current Codex skill and plugin examples, use the OpenAI Plugins repository. If you want to add your own skills to Codex, follow the Build plugins guide, which includes instructions for creating a skill-only plugin.

Agent Skills

Agent Skills are folders of instructions, scripts, and resources that AI agents can discover and use to perform at specific tasks. Write once, use everywhere.

Codex uses skills to help package capabilities that teams and individuals can use to complete specific tasks in a repeatable way. This repository catalogs skills for use and distribution with Codex.

Learn more:

Installing a skill

Skills in .system are automatically installed in the latest version of Codex.

To install curated or experimental skills, you can use the $skill-installer inside Codex.

Curated skills can be installed by name (defaults to skills/.curated):

$skill-installer gh-address-comments

For experimental skills, specify the skill folder. For example:

$skill-installer install the create-plan skill from the .experimental folder

Or provide the GitHub directory URL:

$skill-installer install https://github.com/openai/skills/tree/main/skills/.experimental/create-plan

After installing a skill, restart Codex to pick up new skills.

License

The license of an individual skill can be found directly inside the skill's directory inside the LICENSE.txt file.

View on GitHub

Recent activity

commits and pull requests

Recent open issues

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Code frequency

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Commits per week

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114 commits in the last 52 weeks.

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Commit volume by weekday and hour (UTC). Larger dots mean more commits.
DateListRankStars gained
Sep 17, 2026weekly#14+985
Sep 16, 2026weekly#14+985
Sep 15, 2026weekly#9+1,350
Sep 14, 2026weekly#6+1,622
Sep 13, 2026weekly#5+1,579
Sep 12, 2026weekly#5+1,532
Sep 11, 2026weekly#6+1,490
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Mar 7, 2026daily#15+254
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Feb 9, 2026daily#14+196