Agent Skills

Portable skills for AI coding assistants. Primarily tested with Claude Code and leverages Claude Code-specific features (hooks, context forking), but core functionality works with any Agent Skills-compatible tool including GitHub Copilot, OpenCode, and Cursor.

Installation

Option 1: Install as Plugin (Recommended - For Claude Code)

# Add the marketplace
/plugin marketplace add arvindand/agent-skills

# Install the plugin
/plugin install agent-skills@arvindand-skills

Or test locally:

claude --plugin-dir /path/to/agent-skills

Option 2: Copy to Skills Directory

# Clone and copy skills
git clone https://github.com/arvindand/agent-skills.git
cp -r agent-skills/skills/* ~/.claude/skills/

Works with Claude Code, GitHub Copilot, OpenCode, Cursor, and VS Code with Copilot.

Available Skills

Skill	Description	Use For
context7	Library documentation lookup via Context7 REST API	Getting up-to-date docs for React, Next.js, Prisma, etc.
github-navigator	GitHub operations via gh CLI with deep analysis mode	All GitHub operations + codebase analysis via cloning
maven-tools	JVM dependency intelligence via Maven Tools MCP server	Version checks, upgrade planning, CVE scanning, license compliance
skill-crafting	Create, fix, validate skills + generate from session history	Creating skills, fixing issues, CSO compliance, session-to-skill conversion
ui-ux-design	Create production-grade interfaces with strong UX foundations	Building functional, accessible, visually distinctive UI/UX

Usage

Once installed, skills activate automatically when relevant to your prompt:

You: "How do I use React hooks?"
→ context7 fetches up-to-date React hooks documentation

You: "Show me open issues in facebook/react"
→ github-navigator uses gh CLI to list issues

You: "Analyze the architecture of vercel/next.js"
→ github-navigator clones repo for deep codebase analysis

You: "Should I upgrade Spring Boot from 2.7 to 3.2?"
→ maven-tools analyzes versions, CVEs, breaking changes

You: "Build me a login form with dark mode"
→ ui-ux-design creates accessible component with proper states

You: "Create a skill from this session"
→ skill-crafting evaluates patterns and generates reusable skill

No manual invocation needed — the AI determines when each skill is relevant.

Documentation

See skill-crafting/REFERENCES.md for best practices and patterns.

Cross-Platform Design

Skills use progressive enhancement:

• Core fields (name, description) work everywhere
• Claude Code features should be ignored by other platforms

Claude Code Enhancements

When running in Claude Code, these skills leverage additional features:

Feature	Skills	What It Does
Context forking	github-navigator	Runs in isolated subagent to avoid polluting main context
Stop hooks	skill-crafting, ui-ux-design	Verifies task completion before declaring done
PostToolUse hooks	github-navigator, skill-crafting	Validates output and formats results
Tool restrictions	All	Limits which tools each skill can use

Other platforms get core functionality without these enhancements.

Contributing

Skills I'm looking to collect:

• Frequent operations with zero context overhead
• CLI tools that can be discovered via --help
• Discovery patterns that teach AI dynamically

Note: Would appreciate contributions or references to implementations for other useful skills, especially geared toward helping senior devs focused on backend, architecture, and DevOps.

Why Skills over MCP?

I'm biased towards skills over MCP. Here's why.

Skills are cheaper and at least as effective as MCP tools when done well

MCP loads all tool schemas into every conversation whether you use them or not. Ten tools? That's roughly 1,000 tokens added to every single request. Update: The tool search tool reduces this overhead but it still exists (See https://platform.claude.com/docs/en/agents-and-tools/tool-use/tool-search-tool)

Skills are free until you need them. When a skill triggers, you pay for ~100 words of metadata. That's it.

Anthropic found that using code execution patterns (what skills enable) cut token usage from >150,000 to 2,000. That's a 98.7% reduction. https://www.anthropic.com/engineering/code-execution-with-mcp

If there's a CLI, use a skill

AI models already know how to read --help output. You don't need to write MCP schemas for things like gh, npm, or curl.

Instead, teach the pattern:

• "Run gh issue --help to see what's available"
• "Check npm --help for commands"

The skill stays current as the CLI evolves. No maintenance needed.

See https://simonw.substack.com/p/openai-are-quietly-adopting-skills

When the line is blurry, optimize for cost

Sometimes both approaches work. When in doubt, ask: will I use this frequently? If yes, a skill costs you nothing when idle. An MCP costs you tokens on every request.

When MCP makes sense

Use MCP when:

• Works and well maintained and doesn't contain a gazillion tools
• You need bidirectional communication (push updates, subscriptions)
• Carries complex state and sophisticated caching
• No CLI exists and you can't easily wrap the API

Skills and MCP can work together. You can write a skill that teaches the AI how to use your MCP servers effectively.

License

MIT License — See individual skill LICENSE files for details.

Author: Arvind Menon

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