Automation & agents86/100
mcp builder
anthropics/skills
A planning, implementation and evaluation guide for MCP servers that expose external services to agents.
Repository star change: +586 over 26.7 hours. 2026-11-01
Loop Library
Explore loop library as a automation & agents workflow from alirezarezvani/claude-skills. Compare its source, maintenance and review signals before choosing it for your agent.
What it does
This source provides a task-specific instruction workflow for Automation & agents. Its source file is linked below so you can inspect the exact procedure, tools and dependencies. A full editorial review has not been completed.
Best for
Exploring Automation & agents workflows with an agent. Confirm that the source matches your task and environment.
Tradeoffs and requirements
The automated catalog record does not establish task performance or runtime safety. Check supporting scripts and external services in the source before use.
Unknown; inspect source requirements and supporting scripts.
Install from the source
First time installing a skill? Follow the walkthrough →
Inspect the pinned source snapshot and its supporting files first. The command selects this skill through the open-source skills CLI. Node.js and agent-specific setup may be required. Installation can download code. Catalog ingestion never executes skill instructions or install scripts.
npx skills add https://github.com/alirezarezvani/claude-skills/tree/e4a1dc3695908dd5a6c811cc76ab7aa4cf95f2f0/loop-library --skill loop-libraryReview pinned skill folder ↗ · CLI documentation ↗
After source review, use npx skills check and npx skills update to inspect and apply upstream updates. Re-check changed instructions before running them.
Safety & review signals
Static review only. This is not a security audit or a guarantee of safety.
SKILL.md text only; scripts, dependencies and runtime behavior not audited.
- Network Access — review the source context.
Allowed tools declaration: Unknown. Runtime permissions and network behavior: Unknown.
AI Craft Pad Skill Score
87/100 · Metadata coverage 100% · Model 1.0
Scores summarize observable discovery signals. Popularity and repository activity apply to the whole repository. Unknown runtime safety earns no certification.
- Documentation
- 100/100
- Maintenance
- 100/100
- License Clarity
- 100/100
- Repository Health
- 100/100
- Compatibility Evidence
- 80/100
- Popularity
- 80/100
- Originality
- 80/100
- Static Safety
- 60/100
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