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taeehotaeeho/ClaudeSkills/github-workflow-automation/SKILL.md

github-workflow-automation

Skill0 starsChanged 6 months agoNo licenceView on GitHub

Automate GitHub workflows with AI assistance. Includes PR reviews, issue triage, CI/CD integration, and Git operations. Use when automating GitHub workflows, setting up PR review automation, creating GitHub Actions, or triaging issues.

  • Reads credentials
  • Deletes or force-pushes
  • Commits and pushes

45 other projects use a version of this, 4 of them edited.

Adopted by

Most recently taken up by

Used with

Projects with it also use V3 DDD Architecture, V3 Memory Unification and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • ruvnetSkill

    V3 DDD Architecture

    Domain-Driven Design architecture for claude-flow v3. Implements modular, bounded context architecture with clean separation of concerns and microkernel pattern.

    Also in 27 projects that use this

  • ruvnetSkill

    V3 Memory Unification

    Unify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).

    Also in 27 projects that use this

  • nbossnSkill

    worker-benchmarks

    Run comprehensive worker system benchmarks and performance analysis

    Also in 9 projects that use this

  • ZekiogSkill

    agent-agent

    Agent skill for agent - invoke with $agent-agent

    Also in 5 projects that use this

  • ZekiogSkill

    agent-analyze-code-quality

    Agent skill for analyze-code-quality - invoke with $agent-analyze-code-quality

    Also in 5 projects that use this

  • +3 more from ruvnet
  • +4 more from Zekiog

The file

We split this skill into the rules it gives an agent

8 rules. 0 are common, 7 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 6 edited versions we read keep these.

  • 7

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

“Common” is measured: kept by at least 6 in 10 of the 6 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

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What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

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Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.