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The open agent skills tool - npx skills
This repository page has enough original analysis, source evidence, and comparison context to be treated as an indexable Git-Stars review.
100
review score
Problem solved
It solves the fragmentation of AI agent customization by providing a single, standardized way to distribute and install skills across many different coding agents. It eliminates the need to manually copy configuration files or prompts into each agent's specific directory, and it supports private repositories and multiple source formats, making skill sharing and reuse straightforward.
Deployment reality
The available setup signal starts with: npx skills add vercel-labs/agent-skills. Treat this as a starting point, then ask Codex or Claude to inspect the README, environment variables, runtime version, and deployment target before production use.
Commercial use
The recorded license is MIT. This is a useful commercial-use signal, but teams should still verify license text, dependencies, model/API terms, and trademark constraints.
Capability ceiling
Developers can build and share reusable skill packages that encode best practices, design guidelines, or domain-specific instructions, then install them into any supported agent with a single command. Real-world use cases include enforcing coding standards, providing frontend design guidelines, or adding specialized workflows (e.g., Convex best practices) to agents like Claude Code, Codex, or Cursor. The ceiling is high: with support for 75+ agents and flexible source resolution, it can become the standard package manager for AI agent skills, enabling a rich ecosystem of community-contributed skills.
Git-Stars is independent and not affiliated with GitHub or this project. Analysis may be AI-assisted and based on public repository metadata plus short README-derived summaries. We do not mirror full README files, docs, issues, or social comments.
vercel-labs/skills is tracked as a TypeScript project in the AI Agent area. This evaluation combines public GitHub metadata, category signals, short source summaries, and Git-Stars editorial rules rather than copying project documentation.
Momentum check: the repository has 29k total stars, with +112 today, +0 this week, and +0 this month. These growth windows help distinguish durable adoption from short-lived visibility spikes.
Maintenance check: current activity is Active; the latest push was 13 days ago, and the open issue queue is 1.0k, about 3.53% of total stars. Treat this as an adoption signal, not a substitute for engineering due diligence.
Adoption check: 2.4k forks and 29k watchers suggest how often the project is reused or followed. License signal: MIT. Always verify license compatibility before commercial or internal use.
Practical fit: this project is most relevant when you need TypeScript teams evaluating ecosystem-native tooling. Be cautious when you have low tolerance for large unresolved issue queues.
Source check: Git-Stars currently has 2 explicit source reference(s) for this report and a recent growth signal of 112. Follow the original GitHub repository for final install, security, and release information.
Analysis
ReadyOriginal problem, capability, and verdict guidance are available.
Sources
ReadyRepository metadata and README/source references are attached.
License
ReadyMIT is recorded for review.
Maintenance
ReadyRecent activity is visible in repository metadata.
Alternatives
ReadyEnough nearby projects exist for comparison.
Momentum
29k Stars
Reuse
2.4k Forks
Attention
29k Watchers
Maintenance
active
License
MIT
Open issues
1.0k
skills is a CLI tool for managing and installing skills for AI coding agents like OpenCode, Claude Code, Codex, and Cursor. It supports adding skills from various sources (GitHub, GitLab, local paths) and using them directly without installation.
Key Features
- Supports multiple agents (OpenCode, Claude Code, Codex, Cursor, and 72 more) - Install skills from GitHub, GitLab, any git URL, or local paths - Use skills without installing via `npx skills use`
AI Agent
Agent frameworks, autonomous workflows, and tool-use systems
npx skills add vercel-labs/agent-skills80
Health Score
Active
Commit Activity
Jan 14, 2026
Created
Aug 10, 2026
Last push
+0
Today's growth
+0
7-day growth
+0
30-day growth
Forks
Open
Watchers
vercel-labs
GitHub profileobra/superpowers
An agentic skills framework & software development methodology that works.
affaan-m/ECC
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
NousResearch/hermes-agent
The agent that grows with you
mattpocock/skills
Skills for Real Engineers. Straight from my .agents directory.
anomalyco/opencode
The open source coding agent.
✓
License
✓
Forked
✓ Active
Maintained
Problem Solved
It solves the fragmentation of AI agent customization by providing a single, standardized way to distribute and install skills across many different coding agents. It eliminates the need to manually copy configuration files or prompts into each agent's specific directory, and it supports private repositories and multiple source formats, making skill sharing and reuse straightforward.
Capabilities
Developers can build and share reusable skill packages that encode best practices, design guidelines, or domain-specific instructions, then install them into any supported agent with a single command. Real-world use cases include enforcing coding standards, providing frontend design guidelines, or adding specialized workflows (e.g., Convex best practices) to agents like Claude Code, Codex, or Cursor. The ceiling is high: with support for 75+ agents and flexible source resolution, it can become the standard package manager for AI agent skills, enabling a rich ecosystem of community-contributed skills.
Bottom Line
This tool is ideal for developers and teams who use multiple AI coding agents and want to standardize their instructions or share skills across projects. It is less useful for those who rely on a single agent with built-in customization or prefer manual configuration. The key trade-off is the added abstraction layer and dependency on a third-party CLI, which may introduce complexity for simple use cases.