Fetch dependency source code to give AI agents deeper implementation context. Use when the agent needs to understand how a library works internally, read source code for a package, fetch implementation details for a dependency, or explore how an npm/PyPI/crates.io package is built. Triggers include "fetch source for", "read the source of", "how does X work internally", "get the implementation of", "opensrc path", or any task requiring access to dependency source code beyond types and docs.
npx skills add https://github.com/vercel-labs/opensrc --skill opensrc
Fetches dependency source code so agents can read implementations, not just types. Clones repositories at the correct version tag and caches them globally at ~/.opensrc/.
rg "parse" $(opensrc path zod)
cat $(opensrc path zod)/src/types.ts
find $(opensrc path zod) -name "*.test.ts"
opensrc path <pkg> prints the absolute path to cached source. If not cached, it fetches automatically. Progress goes to stderr, path to stdout, so $(opensrc path ...) works in subshells.
opensrc path zod
opensrc path pypi:requests
opensrc path crates:serde
opensrc path facebook/react
# Multiple packages at once
opensrc path zod react next
opensrc path pypi:requests pypi:flask
opensrc path crates:serde crates:tokio
# Specific versions
opensrc path [email protected]
opensrc path pypi:[email protected]
opensrc path owner/[email protected]
opensrc path owner/repo#main
For npm packages, opensrc auto-detects the installed version from lockfiles (package-lock.json, pnpm-lock.yaml, yarn.lock). Use --cwd to resolve from a different project:
opensrc path zod --cwd /path/to/project
For PyPI and crates.io, explicit versions or latest are used. For repos, use @ref or #ref to pin a branch, tag, or commit.
Source is cached globally at ~/.opensrc/ (override with OPENSRC_HOME).
opensrc list # show all cached sources
opensrc list --json # JSON output
opensrc remove zod # remove a package
opensrc remove facebook/react # remove a repo
opensrc clean # remove everything
opensrc clean --npm # only npm packages
opensrc clean --pypi # only PyPI packages
opensrc clean --crates # only crates.io packages
opensrc clean --packages # all packages, keep repos
opensrc clean --repos # all repos, keep packages
Fetch source when you need to:
Don't fetch source for simple API usage questions that docs or types can answer.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Vendor-agnostic lab automation framework. Use when controlling multiple equipment types (Hamilton, Tecan, Opentrons, plate readers, pumps) or needing unified programming across different vendors. Best for complex workflows, multi-vendor setups, simulation. For Opentrons-only protocols with official API, opentrons-integration may be simpler.
Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox models, Random Survival Forests, Gradient Boosting models, or Survival SVMs, evaluating survival predictions with concordance index or Brier score, handling competing risks, or implementing any survival analysis workflow with the scikit-survival library.
Take vercel-labs/opensrc from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.