By SihaoLiu
Run a structured AI-native development workflow from idea through PR, where each phase creates persistent GitHub artifacts (issues, PRs, project boards) that serve as context for LLM coding agents. Supports research-backed spec drafting, architecture refinement, test-driven issue generation, iterative code-repair loops with third-party AI review, and validated PR merging with cascading issue updates.
Cancel active loop-with-codex-review
Merge a pull request with validation and update related issues
Create a git commit following GAAC format with proper tags and issue references
Start iterative loop with Codex review
Convert implementation plans into test-driven GitHub issues
Document refactoring skill for splitting large markdown files and validating internal links. Use when documents exceed 1000-1500 lines or when checking documentation integrity. Ensures atomic document structure with proper cross-references.
Core GitHub integration skill for GAAC. Manages issues, PRs, project board integration, and PR comments. Provides templates and scripts for all GitHub operations. Use for any GitHub-related actions in GAAC workflows.
Validates GAAC prerequisites and command arguments. Checks for required tools (gh, jq), validates gaac.md configuration, and validates input arguments for all GAAC slash commands. Use before starting any GAAC workflow.
Unified interface for calling external AI tools (Claude CLI, Codex, Gemini) in non-interactive mode. Use for independent code review, idea proposal, design analysis, and other tasks requiring fresh context. Centralizes all third-party tool configuration and permissions.
Executes bash commands
Hook triggers when Bash tool is used
Modifies files
Hook triggers on file write and edit operations
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Runs pre-commands
Runs pre-commands
Contains inline bash commands via ! syntax
Contains inline bash commands via ! syntax
Last Version: 1.1.32
npx claudepluginhub sihaoliu/gaac --plugin gaacOrchestration plugin. v1 use case: async development - turn ready issues into pull requests, then iterate on review feedback until a human takes over. Designed to host more orchestration use cases (refactoring, docs, audits) in future versions.
Structured agentic development methodology - from issue analysis to merge
GitHub issue triage, creation, and management
Git-as-knowledge-graph workflow for traceability across issues, branches, commits, reviews, and PRs.
Git workflows - commits, branches, PRs, issue processing, auto-close detection, and repository management
AI-Driven Engineering workflow commands for managing issues, tasks, implementation, and PRs.