633 skills · sorted by relevance
Review code changes or a repository for actionable bugs by tracing how components interact. Findings explain reachable triggers, incorrect behavior, consequences, and checked counterarguments. Correctness is the default focus; performance and security can also be selected.
Implement a planned game development task by gathering its specifications and design decisions, then assigning the right programming specialist. Coordinate source changes, tests where required, visual evidence, and session state for subsequent review and closure.
Review game code for architecture, coding standards, testability, and performance concerns. Get findings tied to specific code, checks against recorded design decisions, and a report separating required fixes from optional improvements.
Explore relationships between functions and files using a prebuilt code graph, a map of code dependencies. Trace bugs, inspect callers and execution paths, and assess the impact of refactoring or proposed changes.
Review code changes for security, performance, correctness, and maintainability. Get findings tied to files and lines, severity ratings, practical suggestions with code examples, and a recommendation to approve, request changes, or discuss further.
Organizes a code review by giving a reviewer subagent the requirements, a change summary, and the relevant Git commits. It helps check completed work and handle findings by severity before continuing or merging.
Comprehensive GitHub code review with AI-powered swarm coordination
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[omh] Pull request or changes to vet: bug-first review with evidence. Use when the user says: code-review, review, audit, find bugs, release gate, claim audit, evidence audit, README claim.
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Use when receiving code review feedback (especially if unclear or technically questionable), when completing tasks or major features requiring review before proceeding, or before making any completion/success claims. Covers three practices - receiving feedback with technical rigor over performative agreement, requesting reviews via code-reviewer subagent, and verification gates requiring evidence before any status claims. Essential for subagent-driven development, pull requests, and preventing false completion claims.
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Provides comprehensive code review guidance for React 19, Vue 3, Angular 17+, Svelte 5, Rust, TypeScript, Java, Java 8, PHP, Ruby, Rails, Python, Django, FastAPI, Go, C#/.NET, Kotlin, Swift, Dart, Flutter, NestJS, C/C++, Zig, CSS/Less/Sass, Qt, and more. Covers architecture review, performance review, security audit, code quality anti-patterns, and common bugs across all ecosystems. Use when: reviewing pull requests, conducting PR reviews, code review, reviewing code changes, establishing review standards, mentoring developers, architecture reviews, security audits, performance reviews, checking code quality, finding bugs, giving feedback on code.
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Performs a structured five-stage code review covering requirements compliance, correctness, code quality, testing, and security/performance. Each stage uses targeted checklists and categorized feedback (Blocker/Major/Minor/Nit) with actionable suggestions and rationale. Use when the user asks for code review, PR feedback, pull request review, or wants their code checked for bugs, style issues, or vulnerabilities — triggered by phrases like "review my code", "check this PR", "review my changes", "pull request review", or "code feedback".
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Simplify code that works — remove speculative abstraction, dead flexibility, and needless indirection while keeping behaviour identical and verified. Use when a feature has just landed ('now simplify it'), when AI-generated code arrives over-engineered, when a file has grown hard to follow, or as the cleanup pass before review. Produces a smaller, flatter version with identical behaviour, plus a ledger of what was removed and why it was safe. For finding bugs use code-review-checklist / ai-code-review — this skill assumes it works and makes it simple.
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Review AI-authored code for its characteristic failure modes — plausible-but-wrong logic, hallucinated APIs, over-engineering, dead scaffolding, and silent security shortcuts. Use when reviewing an AI-generated or heavily AI-assisted PR, when AI-written code keeps shipping subtle bugs, or when setting review standards for a team using coding agents. Produces a focused review with AI-specific findings, verification steps per risk class, and a team checklist for AI-authored changes. For general PR review use code-review-checklist — this skill covers what that one assumes a human wouldn't do.
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Closeout pass on a finished substantive change — sequence refactor-clean (shape), code-review (diff), and write-docs (docs) so all three run, in the order where each feeds the next. Use after implementing a slice or feature and before calling it done or committing; when the user asks for a final review, a cleanup-and-document pass, or to "review everything." For a diff-only audit, reach code-review directly.
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Code review automation for TypeScript, JavaScript, Python, Go, Swift, and Kotlin. Analyzes PRs for complexity, risk, SOLID violations, and code smells. Use when reviewing PRs, analyzing code quality, or generating review checklists.
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Comprehensive GitHub code review with AI-powered swarm coordination
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Use after gsd-code-review has written REVIEW.md, when you want its Critical and Warning findings fixed. Spawns the fixer agent, commits each fix atomically and writes REVIEW-FIX.md (--all, --auto to iterate).
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Use after a phase's code is written, or when the user asks to review changed files for bugs, security issues, or quality. Spawns the gsd-code-reviewer agent at quick, standard, or deep depth and writes the phase REVIEW.md.
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Comprehensive GitHub code review with AI-powered swarm coordination
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Comprehensive GitHub code review with AI-powered swarm coordination
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Use code-review-graph for local-first CLI/MCP code knowledge graphs, graph-backed code review, structural search, and repository-analysis integrations.
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Evidence-based investigation of issues, bugs, API calls, integrations, and other aspects of software development that need a deep dive to find the root cause and solutions. Use when you need to debug, troubleshoot, diagnose, or figure out why something is broken. Does not review code for quality or style — use code-review for auditing changes or post-code-review-to-pr for posting review feedback to GitHub. Does not assess architectural health or structural risk — use architectural-analysis for architectural concerns. Does not research open-ended options, prior art, or how something works when nothing is broken — use research for that. Does not plan the structural change a root cause calls for — use plan-a-change. Does not map bounded contexts or domain boundaries — use ddd-analysis. Does not capture feedback on Han's own skills — use han-feedback for that.
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Cut a Han release: update CHANGELOG.md with the changes since the last release, bump and tag every plugin that changed as {plugin-name}--v{version} so a version-constrained dependency can resolve, and publish a GitHub release crediting every merged pull request and closed issue to the people behind it. Use when releasing, cutting a release, shipping a new Han version, publishing release notes, or tagging a version. Always stops for approval before creating any tag, because a pushed tag is never moved. Requires the gh CLI, jq, the claude CLI, and a clean git checkout. This is a repository-maintenance skill for the Han repo itself, not a general review or PR skill — use code-review for local review, post-code-review-to-pr to post a PR review, and update-pr-description for PR bodies.
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Generate a PR description from the current branch's changes against a GitHub PR, using the gh CLI. Use when writing, drafting, or updating pull request descriptions, PR summaries, or PR bodies. Does not review code or post review comments — use code-review for local review or post-code-review-to-pr for posting a review to GitHub.
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