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gamAI Skills is a GitHub library of agent workflow folders that its maintainer says contains 992 skills and is published under the MIT license. Each skill is centered on a SKILL.md file with instructions for an AI agent. The collection includes examples for coding, AI workflows, marketing, data, DevOps, and other fields. The count, “production-ready” label, and compatibility claims come from the maintainer; they have not been independently verified across current host releases.
What the collection contains
The gamAI Skills repository describes its library as 992 skills for Claude Code, Cursor, opencode, and other tools that support the Agent Skills format. The maintainer’s September 24, 2026 announcement also states that the collection has 992 skills and is published on GitHub under MIT. These are maintainer-reported figures and claims, not an independent audit of the files or a compatibility test.
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The repository also identifies a “Core 100” starting set. Its examples span AI and agent work such as orchestration, retrieval-augmented generation (RAG), prompt engineering, MCP, and evaluations; software development tasks such as code review, testing, refactoring, APIs, and Git workflows; and web, design, marketing, sales, data, DevOps, cloud, HR, legal, business, finance, security, health, media, and education.
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The repository highlights skills such as task-dag, self-healing-services, report-with-images, invoice and pricing workflows, SEO audit, contract review, cold email, full-output-enforcement, and verification-before-completion. These names and descriptions indicate intended uses; they are not evidence that a workflow performs reliably in a particular project or host.
#1 Best Overall
How an Agent Skill is structured
In the Agent Skills format specification, a skill is a directory containing at least a SKILL.md file. That file has YAML frontmatter followed by Markdown instructions. The required frontmatter fields are name and description; license and compatibility are optional. A skill may also include scripts, reference documents, and other assets.
The format uses progressive disclosure: a host can load a skill’s metadata first, bring in its instructions when the skill is activated, and access supporting resources as needed. This structure can make an individual workflow reusable, but it does not guarantee that every host interprets every feature identically. The specification describes allowed-tools as experimental, with implementation support varying by host.
Rank #2
How to install the skills
The repository documents two routes: adding its marketplace in Claude Code or copying skill folders into a host’s skills directory. It does not provide a version-by-version compatibility matrix, so confirm the current installation path and format support in the documentation for your host before proceeding.
Claude Code marketplace route
- In Claude Code, run the repository’s documented marketplace command:
/plugin marketplace add renatoschust-dot/gamai-skills. - Follow the host’s current plugin or marketplace instructions to locate and enable the skill you want.
- Review that skill’s files and requirements before using it in a project.
Manual folder-copy route
- Open the repository and choose the skill folder you want from
skills/. - For Claude Code, copy the folder into
.claude/skills/. For opencode, Cursor, Windsurf, or another Agent Skills host, use the skills directory specified by that host. - Check the host’s instructions for how it discovers or activates skills, then confirm the skill is available before relying on it.
Folder paths and marketplace behavior can depend on the host and its release. The repository’s README does not establish that one installation path works unchanged across all versions of Claude Code, Cursor, or opencode.
What to check before enabling a skill
A skill is a set of instructions and may include executable files or other dependencies. Treat it as code you are adding to an agent workflow, not as a harmless label or a guarantee of safe output.
- Read the instructions: Inspect the
SKILL.mdfor the actions it asks the agent to take, the scope of its task, and any assumptions about your project. - Inspect supporting files: Check scripts, references, assets, and declared dependencies, especially if a skill can run commands or interact with external services.
- Check permissions: Understand any tools or access the skill expects. The format specification notes that
allowed-toolssupport varies among implementations. - Check host fit: Verify that your specific host supports the format and any features the skill uses; the collection does not provide a version-by-version compatibility matrix.
- Check licensing and provenance: The repository states that it uses MIT licensing and links a license file. Read that file for the actual terms, and review third-party material or dependencies separately. The available claims do not establish independent provenance, safety, compatibility, or quality checks for every item.
- Test on a low-risk task: First see whether the instructions produce an appropriate result in a context where mistakes are easy to catch and have limited impact.
Is the collection a fit for your workflow?
The library may be useful if you want a ready-to-inspect starting point for a recurring agent task and are willing to verify the instructions and host behavior yourself. Its breadth offers examples across technical and nontechnical work, while its Core 100 set gives readers a smaller entry point identified by the maintainer.
It is not, by itself, evidence that a skill has been independently tested, that all 992 files are suitable for production, or that each one works in every named agent. Choose a skill by its task and implementation details, then validate it in your own host rather than relying on the repository’s broad compatibility wording.
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