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google-labs-code/stitch-skills

AI Agent

A library of Agent Skills designed to work with the Stitch MCP server. Each skill follows the Agent Skills open standard, for compatibility with coding agents such as Antigravity, Gemini CLI, Claude Code, Cursor.

7.9k Stars978 Forks16 Open Issues7.9k WatchersTypeScriptApache-2.0
AI AgentMCP ServerDeveloper ToolInfrastructure
Review Readiness

This repository page is useful for visitors, but Git-Stars keeps it out of search indexing until more original evidence and comparison context are available.

75

review score

Needs README summaryNeeds sources
Decision Snapshot

Problem solved

This framework solves the fragmentation of agent capabilities by providing a standardized, interoperable set of skills that work across multiple coding agents. It eliminates the need to reimplement common functionalities for each agent, reducing duplication and ensuring consistent behavior.

Deployment reality

The available setup signal starts with: Install via npm: `npm install @google-labs/stitch-skills` or clone the repo and link locally.. 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 Apache-2.0. 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 agents that perform file operations, code analysis, web scraping, API interactions, and other common development tasks using pre-built skills. Real-world use cases include automated code review assistants, project scaffolding tools, and intelligent debugging helpers. The ceiling is high: with the open standard, developers can create complex multi-step workflows by composing skills, and the library can grow with community contributions.

Source and compliance noteLast synced: Jul 31, 2026

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.

Original GitHub sourceMethodologyEditorial Policy
Editorial Evaluation

google-labs-code/stitch-skills is tracked as a TypeScript project in the AI Agent, MCP Server, Developer Tool, Infrastructure 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 7.9k total stars, with +22 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 Moderate; the latest push was 75 days ago, and the open issue queue is 16, about 0.20% of total stars. Treat this as an adoption signal, not a substitute for engineering due diligence.

Adoption check: 978 forks and 7.9k watchers suggest how often the project is reused or followed. License signal: Apache-2.0. 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 need a legal review, security audit, or production SLA.

Source check: Git-Stars currently has 1 explicit source reference(s) for this report and a recent growth signal of 22. Follow the original GitHub repository for final install, security, and release information.

Evidence Checklist

Analysis

Ready

Original problem, capability, and verdict guidance are available.

Sources

Limited

Needs clearer source references.

License

Ready

Apache-2.0 is recorded for review.

Maintenance

Ready

Recent activity is visible in repository metadata.

Alternatives

Ready

Enough nearby projects exist for comparison.

Best For
  • TypeScript teams evaluating ecosystem-native tooling
Avoid When
  • you need a legal review, security audit, or production SLA
Adoption Signals

Momentum

7.9k Stars

Reuse

978 Forks

Attention

7.9k Watchers

Maintenance

moderate

License

Apache-2.0

Open issues

16

Overview

Stitch Skills is a library of reusable, standardized agent skills designed to work with the Stitch MCP server. It provides a collection of modular capabilities that coding agents like Antigravity, Gemini CLI, Claude Code, and Cursor can leverage to perform common tasks, enabling rapid development and interoperability across different AI coding tools.

Tool Positioning

AI Agent

Agent frameworks, autonomous workflows, and tool-use systems

MCP Server

Model Context Protocol servers, clients, and integrations

Developer Tool

Tools that improve coding, testing, build, and local workflow

Infrastructure

Cloud, deployment, networking, containers, and platform tooling

Quick Start
Install via npm: `npm install @google-labs/stitch-skills` or clone the repo and link locally.
View on GitHub Project Homepage
Project Activity

63

Health Score

Moderate

Commit Activity

Jan 16, 2026

Created

Jul 30, 2026

Last push

Source Trail

GitHub repository metadata

metadata

Star History

Star history will appear after daily syncs accumulate data.

Community Health
978

Forks

16

Open

7.9k

Watchers

Owner
SS

google-labs-code

GitHub profile
Topics & Language
TypeScript
Ecosystem & Usage
GitHub Repository Project Website Search on npm
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License
Apache-2.0
CreatedJan 16, 2026
Last pushJul 30, 2026
Last syncedJul 31, 2026
Repository Standards

✓

License

✓

Forked

~ Moderate

Maintained

AI AnalysisAnalyzed by Git-Stars

Problem Solved

This framework solves the fragmentation of agent capabilities by providing a standardized, interoperable set of skills that work across multiple coding agents. It eliminates the need to reimplement common functionalities for each agent, reducing duplication and ensuring consistent behavior.

Capabilities

Developers can build agents that perform file operations, code analysis, web scraping, API interactions, and other common development tasks using pre-built skills. Real-world use cases include automated code review assistants, project scaffolding tools, and intelligent debugging helpers. The ceiling is high: with the open standard, developers can create complex multi-step workflows by composing skills, and the library can grow with community contributions.

Bottom Line

This project is ideal for developers building AI coding agents who want to avoid reinventing the wheel and ensure compatibility across tools. It may be less useful for those needing highly specialized or non-standard agent behaviors. The key trade-off is standardization vs. flexibility: using these skills constrains you to the defined interfaces but provides interoperability and community support.

Full AI Analysis