VoltAgent/awesome-agent-skills

awesome-agent-skills

A curated collection of 1000+ agent skills from official dev teams and the community, compatible with Claude Code, Codex, Gemini CLI, Cursor, and more.

Stars26,754
Forks2,862
LanguageUnknown
LicenseMIT

Usage guide

awesome-agent-skills is an open-source project around agent-skills, ai-agents, antigravity-skills with 26,754 GitHub stars. This guide focuses on when to use it, how to install it, how to run the first example, and what to verify before adopting it.

Repository license: MITCommercial use permitted, review additional terms

Key features

  • Start from the README minimum path to evaluate integration effort.
  • GitHub detected the MIT repository license, which generally permits commercial use. This signal only covers the repository license; review its obligations and any model weights, datasets, dependencies, or external services before commercial adoption.
  • The project has a homepage, so cross-check docs, examples, and release information beyond GitHub.

Best for

  • Evaluating awesome-agent-skills for the repository language AI workflows.
  • Comparing a GitHub project with 26,754 stars and current repository activity.

Pros

  • awesome-agent-skills has visible GitHub traction with 26,754 stars. Topics: agent-skills, ai-agents, antigravity-skills.
  • The project provides an external homepage for deeper evaluation.

Cons

  • Production fit still depends on documentation depth, issue activity, and release cadence.
  • License review should confirm the MIT terms fit your use case.

Production readiness

awesome-agent-skills should be validated with its README, release history, open issues, and integration requirements before production use.

License risk

MIT is reported by GitHub; review the repository license before redistribution or commercial use.

awesome-agent-skills architecture preview

awesome-agent-skills's main path starts at the entry surface, runs through Coding agent runtime, combines OpenAI / Claude / Gemini, Repository context, GitHub / Discord, and returns Code changes / developer feedback.

Entry

CLI / terminal entry

awesome-agent-skills is primarily entered through a developer command or terminal workflow.

git clone https://github.com/VoltAgent/awesome-agent-skills.git

Runtime

Coding agent runtime

The runtime reads developer intent, inspects repository context, plans edits, and returns code-oriented actions.

coding workflow

Runtime dependencies

Model

OpenAI / Claude / Gemini

Model calls are likely routed through OpenAI, Claude, Gemini based on README and topic signals.

OpenAI, Claude, Gemini

Context

Repository context

Runtime state, user input, repository files, or configuration provide context for each task.

context signal

Tools

GitHub / Discord

Tool adapters let the runtime act outside the model through GitHub / Discord.

GitHub, Discord

Output

Code changes / developer feedback

The final result is code edits, explanations, repository actions, or developer-facing feedback.

coding output

Install tutorial

Before you install

  • A clean working directory for the first test run
1
Step 1

Check the runtime environment

Confirm your system can run a Unknown project before starting the installation steps.

2
Step 2

Get the project files

Start from the official repository or package so the first run matches the documented behavior.

terminal
$ git clone https://github.com/VoltAgent/awesome-agent-skills.git
3
Step 3

Install or build dependencies

No extra setup command was detected. Check the README before adding custom configuration.

Adoption guidance and sources

Practical use cases

Agent workflow prototype

Use it to validate task decomposition, tool calling, memory, tool permissions, and result review loops.

A curated collection of 1000+ agent skills from official dev teams and

This is one of the documented reasons to evaluate awesome-agent-skills before choosing a stack.

Focus area: agent-skills

This is one of the documented reasons to evaluate awesome-agent-skills before choosing a stack.

SKILL project comparison

Compare awesome-agent-skills with similar projects before committing to a stack.

Before adopting

  • Complete one clean-environment verification using the official awesome-agent-skills setup path.
  • Review repository license, model weights, external services, and dependency terms for your use case.
  • Check recent commits, release cadence, issue response, and documentation depth.
  • Evaluate output quality, latency, resource usage, and recovery behavior with a small dataset.

Configuration notes

  • Review README configuration notes before using production data.

Sources checked

These links are used to verify repository, documentation, or tutorial details. Review the source pages before adopting the project.

Troubleshooting

  • If installation fails, first confirm the command is being run from the README-specified directory.
  • If dependencies conflict, retry in a fresh virtual environment, container, or working directory.
  • If output looks wrong, return to the smallest documented awesome-agent-skills example before adding complex data.
  • For keys, model files, or external services, verify environment variables, local paths, and permissions one by one.
  • Before production use, review recent updates, open issues, license terms, and safety boundaries.
What is awesome-agent-skills?

awesome-agent-skills is an open-source skill project. A curated collection of 1000+ agent skills from official dev teams and the community, compatible with Claude Code, Codex, Gemini CLI, Cursor, and more.

How do I install awesome-agent-skills?

Start with the official README. The first detected setup step is: git clone https://github.com/VoltAgent/awesome-agent-skills.git.

Is awesome-agent-skills beginner-friendly?

If you already know the Unknown ecosystem, start with the smallest example. Otherwise test it in an isolated environment first.

Can awesome-agent-skills be used commercially?

GitHub detected the MIT repository license, which generally permits commercial use. This signal only covers the repository license; review its obligations and any model weights, datasets, dependencies, or external services before commercial adoption.

Does awesome-agent-skills need a GPU?

GPU requirements depend on the workload, model, and dataset size. Start with the smallest README example before scaling up.

How should I decide whether to adopt awesome-agent-skills?

Evaluate setup cost, maintenance activity, issue health, license terms, and fit with your real workflow.

Star trend

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