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Welcome to FastSkill

FastSkill is a skills registry and management system that transforms how you discover, install, and manage AI agent skills. Built on the Anthropic/Claude Code skill standard, FastSkill brings the power of modern package managers (like Poetry and npm) to the world of AI agent development.

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The Problem We’re Solving

AI agent skills are scattered across repositories with no standard way to discover, version, or manage them. FastSkill brings package management to AI skills, solving:
  • Discovery: Skills scattered across repos with no search or discovery mechanism
  • Versioning: No version control or reproducible deployments
  • Dependencies: Manual dependency management with runtime conflicts
  • Development: No separation between dev/prod skills or standardized packaging
  • Integration: Each project reinvents skill loading and management

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How FastSkill Solves These Problems

FastSkill extends the Anthropic/Claude Code skill standard into a comprehensive registry system that brings software development best practices to AI agent skills.

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🔍 Semantic Discovery

Find skills by meaning, not just keywords. FastSkill uses OpenAI embeddings to enable semantic search—find skills by what they do, not just what they’re called. This means you can search for “powerpoint presentation” and find skills that create presentations, even if they don’t use those exact words. 
# Semantic search finds skills by meaning
fastskill search "create data visualizations"
# Returns: chart-generator, dashboard-builder, data-plotter

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📦 Package Management for Skills

Declarative skill management, similar to Cargo for Rust or npm for Node.js. FastSkill uses a unified skill-project.toml file at the project root for all configuration, similar to pyproject.toml and package.json: 
# skill-project.toml - Unified configuration
[dependencies]
web-scraper = { source = "git", url = "https://github.com/org/repo.git", branch = "main" }
pytest = { source = "source", name = "team-tools", skill = "pytest", groups = ["dev"] }
Benefits:
  • ✅ Reproducible Installations: skills.lock preserves exact installs
  • ✅ Group-Based Organization: Separate dev/prod skills like Poetry groups
  • ✅ Version Tracking: Track skill versions and update safely
  • ✅ Unified Configuration: Single file for dependencies and repository settings

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🔄 Complete Lifecycle Management

From development to production deployment. FastSkill provides tools for the entire skill lifecycle: 
# Development: Create and test skills
fastskill init                    # Initialize skill metadata
fastskill add ./my-skill -e       # Add in editable mode

# Production: Deploy and manage
fastskill install --without dev   # Install for production
fastskill update                  # Update to latest versions
fastskill show --tree             # View dependency tree

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📊 Smart Dependency Management

Automatic resolution with conflict detection. Skills declare dependencies that FastSkill resolves automatically: 
[dependencies]
web-scraper = { source = "registry", name = "team-tools", version = "^1.0" }
data-processor = { source = "git", url = "https://github.com/org/data.git" }

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🏗️ Development Workflow Integration

Skills as first-class development artifacts. 
# Version control integration
fastskill add https://github.com/org/skill.git
git add skill-project.toml skills.lock
git commit -m "Add data processing skill"

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CI/CD & Team Workflows

Reproducible installations across environments: 
# CI/CD pipeline
- name: Install skills
  run: fastskill install --lock

# Team collaboration
fastskill add --group dev pytest     # Developer adds skill
fastskill install --without dev      # Production deployment

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Multi-Environment Support

Different skill sets for different environments: 
[dependencies]
# Development environment gets extra tools
dev-tools = { source = "source", name = "registry", skill = "dev-tools", groups = ["dev"] }

# Production gets monitoring
monitoring = { source = "source", name = "registry", skill = "monitoring", groups = ["prod"] }

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🚀 Performance Optimizations

Pre-computed embeddings and efficient storage. FastSkill includes performance optimizations that make skill management scalable: Pre-computed Embeddings:
  • Skills can bundle pre-computed embeddings in ZIP packages
  • No API calls needed during installation
  • Faster search and discovery
  • Consistent embeddings across installations
Local Vector Storage:
  • SQLite-based embedding database
  • Fast semantic search without external API calls
  • Offline operation capability
  • Incremental indexing for efficiency

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Expanding the Claude Code Standard

FastSkill builds on the solid foundation of the Anthropic Claude Code skill standard (SKILL.md format) and extends it with:

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1. Registry Infrastructure

The Claude Code standard defines how individual skills are structured. FastSkill adds the infrastructure to manage multiple skills:
  • Source Tracking: Know where each skill came from
  • Version Management: Track versions across installations
  • Repository Support: Multiple skill sources (Git, ZIP, local)

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2. Package Management

Skills become manageable packages:
  • Manifest Files: Declarative skill definitions
  • Lock Files: Reproducible installations
  • Dependency Resolution: Automatic dependency management
  • Group Organization: Environment-based skill grouping

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3. Development Workflow

Skills integrate into standard development workflows:
  • Editable Installs: Local development with symlinks
  • Version Control: Track skills in git
  • CI/CD Integration: Reproducible builds
  • Team Collaboration: Shared skill configurations

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4. Lifecycle Management

Complete lifecycle support:
  • Discovery: Semantic search across skills
  • Installation: From various sources (Git, ZIP, repositories)
  • Updates: Safe version updates
  • Removal: Clean skill removal with dependency checks

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Key Features

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📋 Declarative Configuration

Define your skills declaratively in skill-project.toml at your project root: 
# skill-project.toml
[dependencies]
web-scraper = { source = "git", url = "https://github.com/org/repo.git", branch = "main" }
data-processor = { source = "source", name = "team-tools", skill = "data-processor", groups = ["prod"] }

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🔒 Reproducible Installations

Lock files ensure exact reproducibility: 
# skills.lock - Exact installed state
[[skills]]
id = "web-scraper"
version = "1.2.3"
commit_hash = "abc123def456"
fetched_at = "2024-01-01T12:00:00Z"

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🏷️ Group-Based Organization

Organize skills by environment: 
# Install all skills
fastskill install

# Install without dev group
fastskill install --without dev

# Install only production
fastskill install --only prod

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🔗 Editable Installs

Develop skills locally with symlink support: 
# Install in editable mode
fastskill add ./local-skill -e --group dev

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📚 Source Management

Manage multiple skill repositories: 
# Add a repository
fastskill registry add team-tools --repo-type git-marketplace https://github.com/org/skills.git

# List repositories
fastskill registry list

# Install from source
fastskill install

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🔍 Semantic Search

Find skills by meaning: 
# Search by capability
fastskill search "create presentations"

# Find visualization tools
fastskill search "charts and graphs"

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Use Cases

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Individual Developers

Manage your personal skill library:
  • Track skills you use across projects
  • Version control your skill configurations
  • Update skills safely
  • Discover new skills by capability

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Teams

Share skill configurations:
  • Standardize skill sets across team members
  • Separate development and production skills
  • Track skill updates in version control
  • Collaborate on skill selection

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Organizations

Enterprise skill management:
  • Central skill repositories
  • Version control and auditing
  • Environment-specific skill sets
  • Dependency management at scale

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Skill Authors

Publish and distribute skills:
  • Create versioned skill packages
  • Include pre-computed embeddings
  • Define dependencies
  • Distribute via Git, ZIP, or repositories

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Getting Started

Ready to get started? Here’s a quick path:
  1. Install FastSkill - Get FastSkill set up in your environment
  2. Quick Start Guide - 5-minute setup tutorial
  3. Core Concepts - Understand skills, manifests, and sources
  4. CLI Reference - Complete command documentation

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Why FastSkill?

FastSkill brings software engineering best practices to AI agent skills:
  • ✅ Reproducibility: Lock files ensure consistent installations
  • ✅ Scalability: Manage hundreds of skills across projects
  • ✅ Collaboration: Share skill configurations with teams
  • ✅ Reliability: Version tracking and dependency resolution
  • ✅ Performance: Pre-computed embeddings and efficient storage
  • ✅ Standards-Based: Built on Claude Code skill standard

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What’s Next?

FastSkill: Making AI agent skills manageable, versioned, and reproducible—just like modern software packages.