Introducing SkillUse: A Decentralized Skills Registry for AI Agents

Every organization faces the same challenge: expertise lives in someone's head, scattered across documentation, or buried in Slack threads. When that expert is unavailable, work stalls. When they leave, institutional knowledge disappears.

AI agents like Claude Code introduced Skills—markdown files that give agents domain expertise. But skills created locally stay local. There's no standard way to share, discover, or distribute them.

SkillUse changes that.

What Are Skills, Really?

A skill is more than documentation. It's an executable SOP (Standard Operating Procedure) that empowers AI agents with two complementary capabilities:

Dimension	What It Provides
Domain Knowledge	Expert reasoning, best practices, decision frameworks
Workflow Automation	Executable SOPs that orchestrate agent tools

This dual nature is what makes skills powerful. They encode how experts think and how work gets done.

For Every Knowledge Worker

Skills aren't just for programmers. Any domain expert can encode their expertise:

Copywriters: Brand voice guidelines, content frameworks, editorial standards
Data Analysts: Analysis methodologies, visualization patterns, reporting SOPs
Marketers: Campaign workflows, audience research, content strategies
Product Managers: PRD templates, prioritization frameworks, research protocols
Researchers: Literature review workflows, synthesis frameworks
Engineers: Code review standards, deployment SOPs, architecture patterns

When you install a skill, you're not just sharing documentation—you're sharing how an expert would approach the problem.

Tool Orchestration: The Agent's Hands

Skills orchestrate the agent's native tools to execute workflows:

Tool	Capability
Bash	Execute CLI commands (git, docker, npm, aws, kubectl...)
Read	Access files, configuration, data sources
Write	Create reports, code, documents, structured outputs
WebSearch	Research, fact-checking, current information
WebFetch	Documentation, APIs, external resources

Bash is the universal connector. It bridges the agent to any tool with a command-line interface—version control, cloud infrastructure, databases, CI/CD systems.

This makes skills a natural replacement for workflow automation tools like n8n or Zapier, but with natural language orchestration instead of drag-and-drop UIs.

A Practical Example

Consider a publish skill for releasing software. It doesn't just document the release process—it orchestrates:

Read changelog and version files
Bash run git tag, npm version, gh release create
Write update version numbers across files
Validate CI status before proceeding

The skill encodes both the knowledge (semantic versioning rules, changelog format) and the workflow (the exact commands and sequence).

The Decentralized Registry

SkillUse treats skills as first-class packages—like npm for AI agent capabilities. But instead of a single centralized registry, it uses GitHub repositories as skill sources:

skilluse repo add company/internal-skills    # Private company skills
skilluse repo add anthropics/skill-library   # Public community skills

This enables:

Private skills for proprietary workflows within organizations
Public skills for open-source community patterns
Multi-source configuration mixing internal and external repos

Read + Write: A Complete Ecosystem

Most package managers are consumer-only. SkillUse is designed for both consumption and creation:

# Consume
skilluse search code-review
skilluse install code-review
 
# Create
skilluse repo init myname/my-skills
skilluse publish ./my-skill

This bidirectional flow creates a virtuous cycle: domain experts encode their knowledge into skills, teams consume and refine them, keeping expertise fresh and grounded in real practice.

Multi-Agent Support

Skills aren't tied to a single AI agent. SkillUse installs skills to the correct location based on your current agent:

skilluse agent claude     # Install to ~/.claude/skills/
skilluse agent cursor     # Install to ~/.cursor/skills/
skilluse install review   # Goes to current agent's path

Getting Started

# Install
npm install -g skilluse
 
# Authenticate with GitHub
skilluse login
 
# Add a skill repository
skilluse repo add anthropics/skill-library
 
# Search and install
skilluse search code-review
skilluse install code-review

What's Next

We're building toward a future where:

Every team has a skills repository encoding their best practices
Domain experts—not just engineers—create and share skills
AI agents apply organizational expertise automatically
Workflow automation happens through natural language, not complex UIs

Skills are more than documentation. They're how we scale expertise.

Try SkillUse today and start building your skills registry.