Skills

Skills are reusable instruction packs that extend what your AI coding agents can do. Each skill teaches an agent a specific workflow or domain practice, such as frontend design, database optimization, security review, or multi-agent coordination.

Note: AI DevKit reads your project configuration from .ai-devkit.json. If this file doesn't exist when you run skill add, you'll be prompted to select which AI environments to configure. Skills require at least one skill-capable environment (Cursor, Claude Code, GitHub Copilot, Codex, opencode, Antigravity, Junie, Cline, Devin, Pi, Kilo Code, or Roo Code).

A skill is a folder containing a SKILL.md file and optional supporting resources (scripts, examples, templates). When you install a skill, it's symlinked into your project's skill directory, making it immediately available to your AI agent.

What's a symlink? A symlink (symbolic link) is like a shortcut—instead of copying files, it creates a reference to the original location. This means updates to the cached skill are automatically reflected in your project. On systems where symlinks aren't supported, files are copied instead.

Skills are distributed via Skill Registries—GitHub repositories that follow a standard structure. The AI DevKit maintains a curated list of registries, so you can easily discover and install skills from the community.

You can also browse AI coding agent skills on the web, including built-in AI DevKit skills and installable community skills from supported registries.

AI DevKit ships with a core set of skills in its default registry:

Skill	Purpose
agent-orchestration	Coordinate running AI agents and manage multi-agent workflows
document-code	Document code entry points with structured analysis and dependency mapping
dev-commit	Commit only intended, verified changes with a conventional message
dev-lifecycle	Orchestrate the SDLC workflow and route to phase skills
dev-worktree, dev-requirements, dev-design, dev-planning, dev-implementation, dev-testing, dev-review, dev-pr	Run focused SDLC and publish-for-review phases directly
structured-debug	Follow a disciplined debugging and RCA process before implementing fixes
memory	Use AI DevKit memory operations via CLI patterns when needed
simplify-implementation	Simplify and refactor complex code paths for maintainability
tdd	Apply test-driven development by writing a failing test before production code
technical-writer	Improve docs clarity, readability, and structure
verify	Require fresh terminal evidence before claiming work is complete

You can install these skills the same way you install community skills.

For more detail on the core workflow skills, see the built-in skill pages for dev-lifecycle, structured-debug, tdd, verify, and security-review.

Get up and running in 30 seconds:

# 1. Initialize ai-devkit in your project (if not already done)
ai-devkit init

# 2. Install a skill from a registry
ai-devkit skill add anthropics/skills frontend-design

# 3. Done! Your AI agent can now use the skill.

Once installed, simply ask your AI agent to use the skill's capabilities—it will automatically apply the techniques and patterns defined in the skill.

Skills are currently supported by the following AI coding agents:

Environment	Project Skill Path	Global Skill Path
Cursor	.cursor/skills	~/.cursor/skills
Claude Code	.claude/skills	~/.claude/skills
GitHub Copilot	.github/skills	~/.copilot/skills
Codex	.agents/skills	~/.codex/skills
opencode	.opencode/skills	~/.config/opencode/skills
Antigravity	.agent/skills	~/.gemini/antigravity/skills
Junie	.junie/skills	~/.junie/skills
Cline	.cline/skills	~/.cline/skills
Devin	.devin/skills	~/.config/devin/skills
Pi	.pi/skills	~/.pi/agent/skills
Kilo Code	.kilo/skills	~/.kilo/skills
Roo Code	.roo/skills	~/.roo/skills

Project installs are added inside the current repository. Global installs are added under your home directory and are shared across projects.

Once a skill is installed, AI DevKit places it where the selected agent environment can load it. Then ask the agent to use the skill by name.

When your AI agent starts a session, it reads the SKILL.md files from your project's skill directories. These files contain instructions that teach the agent new capabilities, patterns, or best practices.

Let's say you installed a frontend-design skill. You can now ask your agent:

"Use the frontend-design skill to create a responsive navigation component"

Or simply reference the concepts the skill teaches:

"Build a card component following modern design patterns"

The agent will apply the techniques, conventions, and examples defined in the skill's instructions.

• Be explicit: Mention the skill by name if you want the agent to use specific techniques from it
• Check skill contents: Read the SKILL.md file to understand what capabilities it provides
• Combine skills: Multiple skills can work together—install several to expand your agent's knowledge

Install one or more skills from a registry.

Syntax:

ai-devkit skill add [registry-repo] [skill-name]

Parameters:

• [registry-repo]: The registry identifier (e.g., anthropics/skills). Omit only when using --built-in.
• [skill-name]: Optional skill name to install directly (e.g., frontend-design)

Options:

Option	Description
--built-in	Install all AI DevKit built-in skills
-g, --global	Install the skill into configured global skill paths in your home directory
-e, --env <environment...>	Limit a global install to specific environments; only valid with --global

Examples:

# Install a specific skill into the current project
ai-devkit skill add anthropics/skills frontend-design

# Browse and select one or more skills interactively
ai-devkit skill add anthropics/skills

# Install all AI DevKit built-in skills
ai-devkit skill add --built-in

# Install globally for all configured global environments
ai-devkit skill add anthropics/skills frontend-design --global

# Install globally for specific environments only
ai-devkit skill add anthropics/skills frontend-design --global --env claude codex

This command will:

1. Validate the registry identifier
2. Fetch the merged registry list, or use the built-in AI DevKit registry when --built-in is passed
3. Clone or refresh the cached registry in ~/.ai-devkit/skills/
4. Resolve the skill name directly, or prompt you to select one or more skills in interactive terminals
5. Install the skill into the selected project or global environment paths

Notes:

• If you omit [skill-name] in an interactive terminal, AI DevKit shows a multi-select prompt
• In non-interactive environments, [skill-name] is required
• --env can only be used together with --global

List all skills installed in your project.

Syntax:

ai-devkit skill list

Example Output:

Installed Skills:

  Skill Name       Registry              Environments
  ────────────────────────────────────────────────────
  frontend-design  anthropics/skills     cursor, claude
  api-patterns     vercel-labs/agent-skills  cursor, claude

Total: 2 skill(s)

The list shows:

• Skill Name: The installed skill's name
• Registry: The source registry where the skill came from
• Environments: Which AI environments have this skill installed

This command lists skills installed in the current project only. It does not show skills installed globally with ai-devkit skill add --global.

Remove a skill from your project.

Syntax:

ai-devkit skill remove <skill-name>

Example:

ai-devkit skill remove frontend-design

The cached copy remains in ~/.ai-devkit/skills/ so you can quickly reinstall it in other projects without re-downloading.

This command removes project-installed skills from the current repository. It does not remove skills installed with ai-devkit skill add --global.

To remove a globally installed skill, delete it from the matching global skill path for that environment. For example:

rm -rf ~/.codex/skills/frontend-design

Use the Supported Environments table above to find the correct global path for your agent.

Update skills from registries to get the latest changes.

Syntax:

# Update all cached skill registries
ai-devkit skill update

# Update a specific registry
ai-devkit skill update <registry-id>

Parameters:

• <registry-id> (optional): The registry identifier to update (e.g., anthropics/skills)

Examples:

# Update all registries
ai-devkit skill update

# Update only the anthropics/skills registry
ai-devkit skill update anthropics/skills

How It Works:

The update command pulls the latest changes from skill registries using git pull. It:

1. Scans the cache directory (~/.ai-devkit/skills/) for installed registries
2. Checks if each directory is a git repository
3. Runs git pull to fetch the latest changes
4. Continues updating even if some registries fail
5. Reports a summary of results

When to Update:

• After installing skills: Get the latest improvements and bug fixes
• Periodically: Keep skills up-to-date with community contributions
• Before starting new projects: Ensure you're using the latest patterns

Notes:

• Updates only affect the cached registries in ~/.ai-devkit/skills/
• Since skills are symlinked, updates are immediately available in all projects using those skills
• Non-git directories are skipped (e.g., manually created folders)
• The command continues even if some registries fail to update

Search for skills across all configured registries using keyword matching.

Syntax:

ai-devkit skill find <keyword>

Parameters:

• <keyword>: The search term to match against skill names and descriptions

Options:

Option	Description
--refresh	Force rebuild the skill index before searching

Example:

ai-devkit skill find frontend

How It Works:

The find command searches a pre-built skill index that aggregates skills from all known registries:

1. Checks for a cached local skill index
2. Matches your keyword against skill names and descriptions
3. Returns sorted results showing skill name, registry, and description
4. Provides the install command for easy copy-paste

When to Use --refresh:

• After adding custom registries to your configuration
• When you expect new skills to be available
• If the skill index seems outdated

Notes:

• AI DevKit stores the local skill index at ~/.ai-devkit/skills.json
• Cached index data is reused for up to 24 hours
• If no local index exists, AI DevKit first tries to download a seed index, then falls back to rebuilding it
• Use --refresh to force a rebuild before searching
• Search is case-insensitive and matches partial words

Rebuild the skill index from all registries.

Syntax:

ai-devkit skill rebuild-index
ai-devkit skill rebuild-index --output <path>

Options:

Option	Description
--output <path>	Write the rebuilt index to a custom output path

Examples:

# Rebuild the default local index
ai-devkit skill rebuild-index

# Write the rebuilt index to a custom file
ai-devkit skill rebuild-index --output ./tmp/skills.json

This command is mainly useful for CI, automation, or debugging index issues.

AI DevKit uses a centralized registry file to map registry identifiers to their GitHub repositories. The registry is hosted at:

https://raw.githubusercontent.com/Codeaholicguy/ai-devkit/main/skills/registry.json

You can add your own registries by editing the global AI DevKit config at ~/.ai-devkit/.ai-devkit.json. Custom registries use the same registries map format and are merged with the default registry list. If a registry ID exists in both, your custom entry takes priority.

Example:

{
  "registries": {
    "my-org/skills": "[email protected]:my-org/skills.git",
    "me/personal-skills": "https://github.com/me/personal-skills.git"
  }
}

Once saved, you can install from your custom registry like any other:

ai-devkit skill add my-org/skills internal-skill

The registry is a simple JSON file:

{
  "registries": {
    "anthropics/skills": "https://github.com/anthropics/skills.git",
    "vercel-labs/agent-skills": "https://github.com/vercel-labs/agent-skills.git"
  }
}

Each registry repository should follow this structure:

skills/
├── skill-name-1/
│   ├── SKILL.md           # Required: Main skill instructions
│   ├── scripts/           # Optional: Helper scripts
│   ├── examples/          # Optional: Usage examples
│   └── resources/         # Optional: Additional assets
├── skill-name-2/
│   └── SKILL.md
└── ...

Want to create your own skills? Here's what you need:

Every skill must have a SKILL.md file with YAML frontmatter:

---
name: my-awesome-skill
description: A brief description of what this skill does
---

# My Awesome Skill

Detailed instructions for the AI agent on how to use this skill...

1. Create a GitHub repository with the skills/ directory structure
2. Add your skills with proper SKILL.md files
3. Open a PR to add your registry to the ai-devkit registry

To provide fast installation times, AI DevKit caches skill registries locally:

• Cache Location: ~/.ai-devkit/skills/<registry-id>/
• Behavior: Repositories are cloned once and reused across projects

The registry identifier doesn't exist in the skill registry. Check available registries:

# View the registry file
curl https://raw.githubusercontent.com/Codeaholicguy/ai-devkit/main/skills/registry.json

The skill doesn't exist in the specified registry. Explore the registry repository on GitHub to see available skills.

Your project doesn't have any skill-compatible environments. Run ai-devkit init and select an environment that supports skills (Cursor, Claude Code, GitHub Copilot, Codex, opencode, Antigravity, Junie, Cline, Devin, Pi, Kilo Code, or Roo Code).

The skill folder exists but doesn't contain a SKILL.md file, meaning it's not a valid skill. Contact the registry maintainer.

The registry has local modifications that prevent git pull. To fix:

# Navigate to the registry
cd ~/.ai-devkit/skills/<registry-id>

# Check what changed
git status

# Option 1: Discard local changes
git reset --hard HEAD

# Option 2: Stash changes and update
git stash
git pull
git stash pop

# Then retry the update
ai-devkit skill update <registry-id>

You're trying to update a registry that hasn't been installed yet. Install a skill from that registry first:

ai-devkit skill add <registry-id> <skill-name>

If updates fail due to network issues:

1. Check your internet connection
2. Try updating a specific registry instead of all at once
3. Increase timeout by manually pulling:

cd ~/.ai-devkit/skills/<registry-id>
git pull

This is normal for manually created directories in the skills cache. The update command will skip these automatically. If you want to convert a manual directory to use git:

cd ~/.ai-devkit/skills/<registry-id>
git init
git remote add origin <git-url>
git pull origin main