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git-pro skill

/skills/git-pro

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

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

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SKILL.md
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---
name: git-automation
id: git-automation
version: 2.1.0
description: "Senior DevOps & Automation Specialist. Expert in GitHub Actions, Issue Orchestration, and Advanced Git Internals."
---

# 🤖 Skill: Git Automation (v2.1.0)

## Executive Summary
The `git-automation` expert is responsible for the "Autopilot" layer of the repository. In 2026, manual repository maintenance is a legacy practice. This skill focuses on building robust **GitHub Actions** pipelines, automating **Issue & Project Management**, and leveraging **Git Internals** for deep diagnostics and custom tooling. The goal is a repository that manages itself, allowing engineers to focus on logic rather than plumbing.

---

## 📋 Table of Contents
1. [Core Capabilities](#core-capabilities)
2. [The "Do Not" List (Anti-Patterns)](#the-do-not-list-anti-patterns)
3. [Elite GitHub Actions 2026](#elite-github-actions-2026)
4. [Autonomous Issue Management](#autonomous-issue-management)
5. [Git Internals & Object Forensics](#git-internals--object-forensics)
6. [Automation Toolkit](#automation-toolkit)
7. [Reference Library](#reference-library)

---

## 🚀 Core Capabilities
- **Workflow Orchestration**: designing complex CI/CD pipelines with GitHub Actions.
- **Agentic Issue Tracking**: Using MCP to manage lifecycle of bugs and features.
- **Object Forensics**: Understanding Git internals for complex data recovery.
- **Security Automation**: Implementing secret scanning and OIDC auth in pipelines.
- **Repository Hygiene**: Automated pruning, versioning, and cleanup scripts.

---

## 🚫 The "Do Not" List (Anti-Patterns)

| Anti-Pattern | Why it fails in 2026 | Modern Alternative |
| :--- | :--- | :--- |
| **Manual Issue Creation** | Slow and prone to missing context. | Use **MCP Issue Templates**. |
| **Monolithic Workflows** | Hard to maintain and debug. | Use **Reusable Workflows**. |
| **Hardcoded GH Tokens** | Security risk. | Use **OIDC Connect**. |
| **Ignored Garbage** | Bloats repository size over time. | Run **Automated Pruning Scripts**. |
| **Black-Box Internals** | Leads to "Voodoo Debugging." | Study **Git Object Map**. |

---

## 🏗️ Elite GitHub Actions 2026

-   **Modular Design**: Every task is a reusable job.
-   **Environment Gates**: Protected deployments for production.
-   **AI Reviewers**: Integrated LLM audits on every pull request.

*See [References: GitHub Actions](./references/github-actions-2026.md) for templates.*

---

## 🎫 Autonomous Issue Management

We use MCP to turn requirements into structured artifacts.
-   **Bug Templates**: Mandatory reproduction steps.
-   **Feature Specs**: Linking to `conductor` missions.
-   **Auto-labeling**: Sorting issues by priority and domain.

---

## 📖 Reference Library

Detailed deep-dives into Git Automation:

- [**GitHub Actions 2026**](./references/github-actions-2026.md): Orchestration standards.
- [**Advanced Git Internals**](./references/advanced-git-internals.md): Under the hood of Git 3.0.
- [**Automation Toolkit**](./references/automation-scripts-toolkit.md): High-utility script collection.
- [**Issue Templates**](./references/issue-management-templates.md): Standards for bug and feature tracking.

---

*Updated: January 22, 2026 - 19:10*

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

How do reusable workflows reduce maintenance overhead?

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.