git-pro_skill

This skill automates repository workflows and issue management using GitHub Actions and Git internals to boost efficiency and reliability.
  • Python

7

GitHub Stars

2

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

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Installation

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npx veilstrat add skill yuniorglez/gemini-elite-core --skill git-pro

  • RELEASE-NOTES.md8.5 KB
  • SKILL.md3.2 KB

Overview

This skill transforms repository maintenance into an autonomous, low-friction process. It specializes in building reusable GitHub Actions, automating issue and project workflows, and applying advanced Git internals for diagnostics and recovery. The aim is to let engineers focus on product logic while the repo enforces hygiene, security, and lifecycle rules.

How this skill works

The skill inspects repository configuration, CI workflows, and issue templates to generate modular GitHub Actions and automated issue orchestration hooks. It applies rules for secret scanning, OIDC authentication, and environment gates while scheduling pruning and versioning tasks. For deep debugging it runs Git object forensics and provides actionable diagnostics and repair scripts.

When to use it

  • When CI/CD pipelines become monolithic and slow to iterate
  • When issues and projects need consistent lifecycle automation and labeling
  • When repository size or history requires targeted pruning or recovery
  • When you need secure, tokenless authentication for workflows (OIDC)
  • When code review should include automated LLM-assisted audits

Best practices

  • Design workflows as small, reusable jobs and centralize common logic in reusable workflows
  • Use OIDC and short-lived credentials; avoid hardcoded tokens or secrets in configs
  • Adopt mandatory issue and feature templates to capture reproducible context
  • Enable automated pruning and periodic GC tasks to prevent repository bloat
  • Run Git object forensics only with scoped scripts and backups; document repair steps

Example use cases

  • Convert monolithic CI into modular reusable workflows with environment gates for production deploys
  • Implement MCP-based issue lifecycle: auto-labeling, triage, and feature-spec linking to missions
  • Add secret scanning and OIDC authentication to all workflows to eliminate long-lived tokens
  • Schedule automated pruning and packfile maintenance to reduce repo size and improve clone times
  • Create diagnostic jobs that run git fsck/object mapping and produce remediation playbooks

FAQ

Breaking pipelines into small reusable jobs isolates responsibilities, simplifies debugging, and lets multiple repositories share vetted logic without duplicating code.

Is it safe to run automated pruning?

Yes if you run pruning with explicit retention rules, backups, and preflight checks. Always test pruning in a staging mirror and document rollback steps.

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git-pro skill by yuniorglez/gemini-elite-core | VeilStrat