Skillbase / spm

Skills Package Manager — install, share, and manage reusable AI skills across any MCP-compatible client.

What is spm?

spm is a package manager for AI skills. Skills are structured instructions — not code — that teach AI models how to perform specific tasks: code review, security audits, API design, prompt engineering, DeFi analysis, and more.

npm install -g @skillbase/spm

spm connects to your AI client via MCP (Model Context Protocol), giving your AI access to a registry of community-contributed skills that load on demand.

Unlike npm-based approaches that piggyback on node_modules, spm has its own registry, its own format, and works with any AI client — not just code editors.

Already using Vercel Skills? spm is fully compatible — spm add owner/repo/skill-name and you're done. Auto-converts, no extra steps. See details below.

Quick start

# Install
npm install -g @skillbase/spm

# Initialize in your project
spm init

# Connect to your AI client
spm connect claude       # Claude Desktop / Claude Code
spm connect cursor       # Cursor
spm connect vscode       # VS Code (Copilot)
spm connect windsurf     # Windsurf
spm connect jetbrains    # Any JetBrains IDE

# Install a skill
spm add skillbase/arch-code-review

# Install a persona (a bundle of skills with a defined role)
spm persona add skillbase/sec

Once connected, your AI automatically discovers and loads skills when it encounters a matching task. No manual invocation needed.

How it works

spm registers as an MCP server. Your AI client gets five tools:

Lazy loading is key to the design. The AI sees a lightweight index of all installed skills. When it encounters a task that matches a skill's trigger, it loads just that skill's full instructions. This keeps context windows clean and lets you install dozens of skills without overhead.

User: "Review this pull request for architecture issues"
  ↓
AI sees skill_list → finds arch-code-review (trigger matches)
  ↓
AI calls skill_load("arch-code-review")
  ↓
Full review methodology loads into context
  ↓
AI performs structured code review

What's inside a skill?

A skill is a directory. At its core is a SKILL.md file — structured Markdown with YAML frontmatter:

---
name: arch-code-review
version: 1.0.3
description: "Architecture-aware code review"
tags: [code-review, architecture, solid, complexity]
triggers:
  - "code review"
  - "architecture review"
  - "pull request review"
---

# Code Review Methodology

## Evaluation criteria
- Coupling/cohesion at module and class level
- SOLID principle adherence
- Cyclomatic complexity hotspots
...

But a skill isn't limited to instructions. The directory can also contain auxiliary scripts, templates, example files, and any other resources the AI needs during execution. Think of SKILL.md as package.json — it's the entry point, but the whole directory is the package.

Skill features

• Semver versioning — skillbase/arch-code-review@1.0.3
• Dependencies — skills can depend on other skills
• Auxiliary files — scripts, templates, reference data bundled alongside instructions
• Triggers — descriptions and file patterns that help the AI decide when to load
• Tags — for search and discovery
• Confidence scores — computed from real user feedback via skill_feedback

Personas

A persona bundles multiple skills into a complete AI identity with a defined role, tone, and expertise area.

spm persona add skillbase/sec

This installs the Security Auditor persona with its dependencies: smart-contract-audit, appsec, and web3-threat-modeling. When activated, the AI assumes the persona's role and has access to all bundled skills.

Available personas:

Team sync

Skillbase Sync adds team-level configuration and knowledge sharing on top of spm. Define a standard skill set for your project — everyone installs with one command.

# Link your repo to a Sync project
spm sync init

# Install everything the project requires
spm sync

# Check what's missing without installing
spm sync --status

When Sync is connected, your AI agent also gets access to shared team knowledge — decisions, constraints, and context captured by teammates. No more starting from scratch when someone else picks up a task.

Learn more: Sync documentation

Registry

The registry hosts skills across several domains:

Development — python-backend, python-testing, db-mongodb, arch-code-review, arch-api-design, arch-system-design

Security — appsec, smart-contract-audit, web3-threat-modeling, prompt-injection-detector, jailbreak-scanner, prompt-safety-validator

DeFi & Trading — yield-analysis, leverage-calc, onchain-signals, mev-awareness, trade-journal

Growth & Strategy — defi-growth-strategy, growth-airdrop-design, web3-grant-writing

Meta — prompt-engineering-craft (learn to write better prompts and skills)

Browse the full registry: skillbase.space/explore

Vercel Skills compatibility

spm is fully compatible with Vercel Skills and any GitHub-hosted skills that follow the same SKILL.md format. You don't have to choose — if a skill exists on GitHub, you can use it in spm.

Install directly — one command, auto-converts and installs:

spm add vercel-labs/agent-skills/web-design-guidelines

That's it. spm fetches the skill from GitHub, detects the format, converts it to SPM on the fly, and installs it locally. Ready to use immediately — no flags, no extra steps.

Or convert first, then publish — if you want to review, edit, and share with the community:

# 1. Fetch and convert to a local directory
spm convert vercel-labs/agent-skills/web-design-guidelines -o ./

# 2. Review and edit SKILL.md if needed
# 3. Publish to the spm registry
spm publish ./web-design-guidelines

Author defaults to the GitHub repo owner. Override with --author <name> if needed. The --skill <name> flag is also supported as an alternative: spm add vercel-labs/agent-skills --skill web-design-guidelines.

What spm adds on top of the original skill:

You can also list all available skills in a repository before installing:

spm convert vercel-labs/agent-skills
# → lists all skills in the repo's skills/ directory

Works with any GitHub repo that contains SKILL.md files — not limited to Vercel's repositories.

Publish your own skill

From the CLI:

# Scaffold a new skill from scratch
spm create my-skill

# Or convert an existing prompt file
spm convert my-prompt.md --author myname

# Or import from GitHub (auto-converts Vercel Skills)
spm convert owner/repo/skill-name -o ./

# Edit SKILL.md, then publish
spm publish

From Skillbase Studio:

Skillbase Studio provides a visual editor for creating, testing, publishing, and installing skills — all in the browser. Studio communicates with your local spm daemon to publish and install directly from the UI.

1. Create or import a skill in Studio
2. Edit and test with the built-in sandbox
3. Click Publish — Studio sends the compiled SKILL.md to your local spm, which handles registry auth and upload
4. Click Install — installs the published version locally via spm

Studio requires spm to be running locally (spm status-server start or click "Connect spm" in the UI). All publishing uses your existing spm login credentials.

Skills are free to publish and free to use. The registry is open.

Supported clients

spm works with any client that supports MCP:

Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, Cline, Roo Code, JetBrains IDEs (all), Zed, OpenAI Codex, Emacs, Neovim, and others.

# See all supported clients
spm connect --list

Why not just use npm?

Some projects bundle AI skills inside npm packages. spm takes a different approach:

• Own registry — skills are first-class citizens, not a side-effect of npm install. Discovery, search, versioning, and confidence scores are built in.
• Not tied to Node.js — spm skills work with any AI client on any platform. You don't need a node_modules folder.
• Lazy loading via MCP — skills load into AI context on demand, not all at once. This is critical when you have dozens of skills.
• Feedback loop — skill_feedback lets users rate skills. Confidence scores surface the most effective skills.
• Personas — bundle skills into roles. npm has no concept of this.
• Extensible format — a skill can grow from pure instructions to include scripts, templates, and data without changing how it's installed or loaded.
• Compatible, not locked-in — import skills from Vercel Skills, GitHub, or local prompt files. spm convert handles format conversion automatically.

Security

All skills and personas in the public registry go through a security review before publication. Auxiliary files bundled with skills are scanned with antivirus and additional automated security tooling. spm uses token-scoped authorization for publishing — only verified authors can update their packages.

The SKILL.md format is plain Markdown with structured metadata — there's no postinstall script execution or hidden side effects.

Contributing

We welcome skills, bug reports, feature requests, and documentation improvements.

• Open an issue
• Start a discussion
• Publish a skill

Links

• skillbase.space — spm homepage and registry
• Skillbase Sync — team knowledge sharing and project configuration
• Skillbase Studio — visual editor for creating, testing, and publishing skills
• Skillbase Workspace — marketplace for ready-made AI agent teams; publish your own and earn revenue share on every deployment
• Documentation
• npm

License

MIT — see LICENSE.