agent-reach
Skill2 starsChanged 5 months agoNo licenceView on GitHub
Give your AI agent eyes to see the entire internet. 17 platforms via CLI, MCP, curl, and Python scripts. Zero config for 8 channels.
Other versions43 projects use a version of this.
Word for word · 4
- imagedl/claude-skills★ 1100% same
- zkw15555506767-boop/claude-skills★ 1100% same
- sueryue/Claude-Skillls★ 0100% same
- yueouLi/claude-skills★ 0100% same
Edited · 18
- Ootto-AI/claude-content-skills★ 28031% same
- TencentBlueKing/bk-lite★ 6235% same
- justinjohnson25600/hermes_skills★ 1421% same
- ClaireAll/skills★ 216% same
- neurise-io/neurise-adseo★ 231% same
- qihangzhang-272/agent-skill-library★ 230% same
- RobSpct/agentic-os-rs-community-kit★ 210% same
- yukicoding/skills★ 235% same
- BlueChonk/BlueChonk-skills★ 125% same
- leishifu666/skills★ 127% same
8 more not listed
Wrote their own version · 21
- zengwenliang416/ppt-agent★ 833same name
- GPTtang/skill-atlas★ 4same name
- Jichi666/agent-reach-skill★ 4same name
- seasky7c/legal-skills★ 4same name
- ankul5/internship-hunt-skill★ 2same name
- bushuhui/skills★ 2same name
- jonahobiman/agent-reach★ 2same name
- Taffyreclaimed45/ppt-agent★ 2same name
- ChianW/C31★ 1same name
- gusibi/skills★ 1same name
11 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria. Based on https://github.com/multica-ai/andrej-karpathy-skills.
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Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
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