Total 54,172 skills, Code Quality has 2444 skills
Showing 12 of 2444 skills
Create a detailed refactor plan with tiny commits through user interviews, then file it as a GitHub issue. Use this when the user wants to plan a refactor, create a refactoring RFC, or break a refactor into safe incremental steps.
Eight-axis judgment code review for the current diff — Correctness, Simplification, Tests, Documentation, Style, Intent, Design/API, Performance (+ Coherence on metadata changes). Five-phase pipeline scope → deterministic tool battery (npx/uvx-preferred, zero-install for the JS + Python majority) → 8 parallel LLM axis reviewers → Haiku validators on sub-80 findings (verbatim rubric, ≥80 threshold) → synthesis with no-silent-drop + Conventional Comments JSONL. Every report closes with "What I did NOT check" (security → /security-review, runtime perf, flaky detection). Opt-in flags `--verify-build`, `--mutation-test`, `--reconcile`, `--apply-safe`. Public-skill posture — zero auto-install, graceful skip on missing native tools.
Performs AI-powered code review on Git changes using the `ocr` CLI from alibaba/open-code-review. Use when the user asks to review code, review a pull request, review staged/unstaged changes, review a commit, or compare branches for code quality issues. Produces line-level review comments and can automatically apply fixes when requested. With appropriate review rules, can detect various types of issues including bugs, security vulnerabilities, performance problems, and code quality concerns.
Roblox Luau Development Workflow for implementing, reviewing, and refactoring Roblox game scripts, ModuleScript, ServerScript, LocalScript, RemoteEvent/RemoteFunction, DataStore, and server/client layering. Use when working on Roblox, Luau, Roblox Studio code, Rojo-synced scripts, gameplay systems, UI scripts, replication, remotes, or Roblox services.
Review generated or changed production code before it ships, using Clean Code, SOLID, DRY, KISS, YAGNI, and LLM-specific failure-mode checks in any programming language. Best used reactively after an agent writes, edits, refactors, or fixes code, before presenting, committing, or merging the result. Use when the user asks "review this PR", "is this safe to merge?", "make this cleaner", "audit this code", "refactor this", "fix this bug", or after a coding agent produced implementation code. Can also guide writing when explicitly invoked before a risky edit. DO NOT USE for factual/conceptual questions, CI/tooling config, git workflow, running/debugging tests, pure architecture discussion, prose writing, data analysis, or test-code review (use test-guard).
Use before claiming work is complete, fixed, or tested; before committing or creating a PR — you must run verification commands and confirm the output before claiming success; always back up assertions with evidence
Use this skill when a user asks to review a pull request for bugs, wants AI code review focused on correctness issues, or runs /bug-review. Trigger on PR review, bug finding, code review, "review this PR", "check for bugs", "find issues in this PR". This is a multi-pass review workflow with 5 parallel passes, majority voting, independent Opus validation, and resolution rate tracking. Also trigger on /bug-review:resolve to classify whether findings were fixed at merge time, and /bug-review:report for resolution rate stats. Even if the user just says "review this" while on a PR branch, trigger this skill.
Reviewer-only pass for /plan --review and cleanup artifact review
Discover and understand project rules, coding standards, and architectural guidelines before starting a task. Use when you need to know the constraints, patterns, or compliance requirements for a feature, file, or technology.
Execution-aware preflight analysis (control-flow, timing/energy) on existing callees using compiled artifacts, to catch problems while the design is still cheap to change.
Stack-aware review for local diffs, pull requests, and repository-wide audits. Routes review across shared policy plus language packs for TypeScript frontend, TypeScript backend/Bun, Go, Rust, and Python. Use after implementation, before merge, or when auditing an existing codebase.
Validates and scores Claude Code skill packages for quality, completeness, and best practices compliance. Tests Python scripts, checks YAML frontmatter, and generates quality reports. Use when creating new skills, validating skill packages, or auditing skill quality.