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Review code changes and pull requests for correctness, security, performance, and test quality. The skill helps prioritize issues, write specific and constructive feedback, and create shared review checklists and standards for a development team.
Review code changes and pull requests for correctness, security, performance, and test quality. The skill helps prioritize issues, write specific and constructive feedback, and create shared review checklists and standards for a development team.
Leverage OpenAI Codex/GPT models for autonomous code implementation, code review, and plan review. Triggers: "codex", "use gpt", "gpt-5", "let openai", "full-auto", "adversarial review", "second opinion review", "用codex", "让gpt实现", "对抗式审查", "让codex审查计划", "第二意见". Use this skill whenever the user wants to delegate coding tasks to OpenAI models, run code or plan reviews via codex, get a second-opinion review from a different model, or execute tasks in a sandboxed environment.
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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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Run an independent code review using the OpenAI Codex CLI in headless mode. Gets a second opinion from a different model family (the current Codex models) on recent changes, a PR, a commit, or the whole app — covering bugs, regressions, security, data consistency, UX/state bugs, performance risks, and testing gaps. Saves a severity-prioritised report to .jez/reviews/. Triggers: 'codex review', 'review with codex', 'independent code review', 'what does codex think', 'get codex to review'.
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Drive a PR to an approved code review by looping OCR's multi-agent review and address steps. Runs /ocr:review then /ocr:address repeatedly until the review verdict is APPROVE, then one final /ocr:address for leftover suggestions, posting every review and every address round to the GitHub PR as comments. Use when the user asks to 'review and address in a loop', 'iterate review until approved', 'auto review-and-fix this PR', 'loop /ocr:review and /ocr:address', or to take a changeset all the way to a clean APPROVE with the default reviewer team. Wraps the /ocr:review (.ocr/commands/review.md) and /ocr:address (.ocr/commands/address.md) skills; needs a feature branch with an open GitHub PR and the gh CLI for posting.
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Multi-agent code review using the Pragmatic Quality framework. Orchestrates parallel review agents (CLAUDE.md compliance, bug scanning, git history, security) with independent confidence scoring to produce high-signal findings. Use when user runs /code-review, /review:code-review, requests a "code review", "review my changes", "PR review", or mentions "review diff", "review branch".
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OpenAI Codex CLI wrapper — three modes. Code review: independent diff review via codex review with pass/fail gate. Challenge: adversarial mode that tries to break your code. Consult: ask codex anything with session continuity for follow-ups. The "200 IQ autistic developer" second opinion. Use when asked to "codex review", "codex challenge", "ask codex", "second opinion", or "consult codex". (gstack) Voice triggers (speech-to-text aliases): "code x", "code ex", "get another opinion".
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Configure Codex CLI to connect through OmniRoute on Linux, macOS, or Windows. The workflow detects the operating system and shell, creates configuration files and seven profiles, sets environment variables, and verifies the setup.
Run a final pull request review using separate agents for each available review skill. Collect all reported issues into a numbered Markdown list, with a specific file path and line number for every finding.
Launch the Remotion documentation site locally and open it in the Codex in-app browser. The workflow installs dependencies, builds the project, starts Docusaurus, and reports the actual preview URL and server status.
Review a GitNexus pull request for production readiness with seven coordinated reviewer agents. Combine their findings and have a final critic check the draft, producing a review without editing code or posting results.
Let the host AI agent review Git changes while ocr selects files and resolves review rules. Receive findings grouped by severity, plus coverage details showing which files were reviewed or skipped and why.
Review code for security, performance, quality, and maintainability. Get findings organized by severity, with file locations, explanations of impact, and example fixes, plus code metrics and complexity comparisons for refactoring reviews.
Review code for security, performance, quality, and ease of maintenance. Receive an overall assessment and categorized findings, with file locations, severity, impact, and code examples for addressing critical issues.
Review a defined code change through independent code and architecture reviewers. Receive severity-rated findings with file and line references, concrete fixes, and a final recommendation on whether the change is ready to merge.
Build or refresh a knowledge graph, a map of code relationships used for code review. Choose a full rebuild or an incremental update, then report the operation's status and summary.
Have a different AI model review code, analysis, or documents against the original skill's stated requirements. Receive evidence-based findings and a comparison of agreement and disagreement, then decide which recommendations to accept.
Set up Herdr Kit and its Mastra Code integration, manage repository synchronization, and create or remove managed worktrees, separate working copies for review or development. The workflow checks supported operations and verifies the resulting manager state.
Review Qwen Code issues and pull requests through staged checks. Assess product fit, code simplicity, and CI evidence, then prepare English and Chinese comments that explain findings and flag decisions needing maintainer attention.
Delegate code exploration, feature development, bug fixes, and reviews to Qwen Code through acpx, a command-line client for communicating with agents. Use ongoing sessions, separate task sessions, and structured output to coordinate development work.
Review code changes or a pull request for bugs, effects on existing behavior, test gaps, and project standards. Receive findings supported by the code and a clear account of review coverage, with local fixes available when explicitly requested.
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.
Get critical feedback on research ideas, papers, and experimental results from an external AI reviewer. Repeated discussions help identify unsupported claims, plan missing experiments, and document agreed improvements with priorities and estimated computing costs.