Git & Pull Requests subagents

Create clear, comprehensive CLI documentation for RTK with focus on usability, performance claims, and practical examples

Use this agent when you need comprehensive code quality assurance, security vulnerability detection, or performance optimization analysis. This agent should be invoked PROACTIVELY after completing logical chunks of code implementation, before committing changes, or when preparing pull requests. Examples:\n\n<example>\nContext: User has just implemented a new filter for RTK.\nuser: "I've finished implementing the cargo test filter"\nassistant: "Great work on the cargo test filter! Let me use the code-reviewer agent to ensure it follows Rust best practices and token savings claims."\n<uses code-reviewer agent via Task tool>\n</example>\n\n<example>\nContext: User has completed a performance optimization.\nuser: "Here's the optimized lazy_static regex compilation"\nassistant: "Excellent! Now let me invoke the code-reviewer agent to analyze this for potential memory leaks and startup time impact."\n<uses code-reviewer agent via Task tool>\n</example>\n\n<example>\nContext: User has written a new cross-platform shell escaping function.\nuser: "I've created the escape_for_shell function with Windows support"\nassistant: "Perfect! I'm going to use the code-reviewer agent to check for shell injection vulnerabilities and cross-platform compatibility."\n<uses code-reviewer agent via Task tool>\n</example>\n\n<example>\nContext: User has modified RTK hooks for Claude Code integration.\nuser: "Updated the rtk-rewrite.sh hook"\nassistant: "Important changes! Let me immediately use the code-reviewer agent to verify hook integration security and command routing correctness."\n<uses code-reviewer agent via Task tool>\n</example>\n\n<example>\nContext: User mentions they're done with a filter implementation.\nuser: "The git log filter is complete"\nassistant: "Excellent progress! Since filters are core to RTK's value, I'm going to proactively use the code-reviewer agent to verify token savings and regex patterns."\n<uses code-reviewer agent via Task tool>\n</example>

Use this agent when encountering errors, test failures, unexpected behavior, or when RTK doesn't work as expected. This agent should be used proactively whenever you encounter issues during development or testing.\n\nExamples:\n\n<example>\nContext: User encounters filter parsing error.\nuser: "The git log filter is crashing on certain commit messages"\nassistant: "I'm going to use the debugger agent to investigate this parsing error."\n<commentary>\nSince there's an error in filter logic, use the debugger agent to perform root cause analysis and provide a fix.\n</commentary>\n</example>\n\n<example>\nContext: Tests fail after filter modification.\nuser: "Token savings tests are failing after I updated the cargo test filter"\nassistant: "Let me use the debugger agent to analyze these test failures and identify the regression."\n<commentary>\nTest failures require systematic debugging to identify the root cause and fix the issue.\n</commentary>\n</example>\n\n<example>\nContext: Performance regression detected.\nuser: "RTK startup time increased to 25ms after adding lazy_static regex"\nassistant: "I'm going to use the debugger agent to profile the performance regression."\n<commentary>\nPerformance problems require systematic debugging with profiling tools (flamegraph, hyperfine).\n</commentary>\n</example>\n\n<example>\nContext: Shell escaping bug on Windows.\nuser: "Git commands work on macOS but fail on Windows with shell escaping errors"\nassistant: "Let me launch the debugger agent to investigate this cross-platform shell escaping issue."\n<commentary>\nCross-platform bugs require platform-specific debugging and testing.\n</commentary>\n</example>

Complete pull request lifecycle management and GitHub workflow coordination

Cross-repository swarm orchestration for organization-wide automation and intelligent collaboration

Pull request swarm management agent that coordinates multi-agent code review, validation, and integration workflows with automated PR lifecycle management

Implements comprehensive security mechanisms for distributed consensus protocols

Synchronize AI swarms with GitHub Projects for visual task management, progress tracking, and team coordination

Comprehensive GitHub integration modes for workflow orchestration, PR management, and repository coordination with batch optimization

Hive-mind collective decision making with Byzantine fault-tolerant consensus, attention-based coordination, and emergent intelligence patterns

Orchestrate complex software releases using AI swarms that handle everything from changelog generation to multi-platform deployment

Applies researched improvements to Claude Code components, validates changes with the component-reviewer agent, and creates pull requests. The only agent that modifies files and creates PRs.

Assists with deploy verification and troubleshooting. Deployments happen automatically via GitHub Actions on push to main. Use when the user needs to check deploy status or debug deploy issues.

Migrates components (agents, commands, skills, hooks, settings, MCPs) from external GitHub repositories to claude-code-templates, validates them with component-reviewer, and regenerates the catalog

Prototyping specialist. Builds throwaway implementations at two points in the workflow: (1) concept prototypes right after brainstorm to validate an idea is fun before writing GDDs (/prototype), and (2) vertical slices in pre-production to validate the full game loop before committing to Production (/vertical-slice). Standards are intentionally relaxed for speed.

You are the independent verifier for the Changelog Drafter loop.