Code Review & Quality

Ultra-compressed code review comments. Cuts noise from PR feedback while preserving the actionable signal. Each comment is one line: location, problem, fix. Use when user says "review this PR", "code review", "review the diff", "/review", or invokes /caveman-review. Auto-triggers when reviewing pull requests.

Ultra-compressed commit message generator. Cuts noise from commit messages while preserving intent and reasoning. Conventional Commits format. Subject ≤50 chars, body only when "why" isn't obvious. Use when user says "write a commit", "commit message", "generate commit", "/commit", or invokes /caveman-commit. Auto-triggers when staging changes.

Remove unused code from this project with ultrawork mode, LSP-verified safety, atomic commits. Triggers: remove dead code, dead code, cleanup, remove unused.

一个全面的 Claude Code 会话验证系统。

Verification loop for Spring Boot projects: build, static analysis, tests with coverage, security scans, and diff review before release or PR.

Verification loop for Django projects: migrations, linting, tests with coverage, security scans, and deployment readiness checks before release or PR.

Implement memory-safe programming with RAII, ownership, smart pointers, and resource management across Rust, C++, and C. Use when writing safe systems code, managing resources, or preventing memory bugs.

Master ShellCheck static analysis configuration and usage for shell script quality. Use when setting up linting infrastructure, fixing code issues, or ensuring script portability.

Master defensive Bash programming techniques for production-grade scripts. Use when writing robust shell scripts, CI/CD pipelines, or system utilities requiring fault tolerance and safety.

Python resilience patterns including automatic retries, exponential backoff, timeouts, and fault-tolerant decorators. Use when adding retry logic, implementing timeouts, building fault-tolerant services, or handling transient failures.

Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.

Common Python anti-patterns to avoid. Use as a checklist when reviewing code, before finalizing implementations, or when debugging issues that might stem from known bad practices.

Manage major dependency version upgrades with compatibility analysis, staged rollout, and comprehensive testing. Use when upgrading framework versions, updating major dependencies, or managing breaking changes in libraries.

Master systematic debugging techniques, profiling tools, and root cause analysis to efficiently track down bugs across any codebase or technology stack. Use when investigating bugs, performance issues, or unexpected behavior.

Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.

Use this skill when implementing tasks according to Conductor's TDD workflow, handling phase checkpoints, managing git commits for tasks, or understanding the verification protocol.

PR Code Review (Local): perform a thorough local code review with full project context. Use when: (1) User asks to review a PR, (2) User says "/pr-review", (3) User wants to review code changes before merging.

PR Review Fix: automatically fix all issues identified in a pr-review report. Use when: (1) User says "fix all review issues", (2) User says "/pr-fix", (3) After pr-review skill has produced a report, (4) User wants to address PR review feedback.

Auto-fix high-frequency Sentry issues: fetch issues > N occurrences, analyze stack traces, fix code, create GitHub issues, and submit PRs. Supports user feedback issues (event.type "default") with attachment analysis (logs, screenshots) when include_feedback=true. Use when: (1) User says "/fix-sentry", (2) User asks to fix Sentry issues.

Auto-fix GitHub issues labeled as bugs: fetch open bug issues, analyze feasibility, fix code, and submit PRs. One issue per invocation. Use when: (1) User says "/fix-issues", (2) User asks to fix GitHub issues.

Use this skill to run npm run lint and fix linting issues. Triggers on fixing lint errors after code changes or validating code against project style guidelines.

Perform a release-readiness review by locating the previous release tag from remote tags and auditing the diff (e.g., v1.2.3...<commit>) for breaking changes, regressions, improvement opportunities, and risks before releasing openai-agents-python.

Run the mandatory verification stack when changes affect runtime code, tests, or build/test behavior in the OpenAI Agents Python repository.

Review only changes since last commit using impact analysis. Token-efficient delta review with automatic blast-radius detection.