Results for “code review”

Delegate code review to a subagent running a specific model. Use ONLY when user explicitly names a model to review changes ("review with opus", "use sonnet to review", "review with gemini"). The root agent reconstructs changes from conversation history and spawns a subagent with the code-review skill using the specified model. Do NOT use for general code review (use code-review skill instead), for reviewing PRs from git history, or when no model is specified by the user.

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Independent review loop run before delivery in code work. An independent reviewer (Codex, or fresh Codex-style subagents) reads the whole PR against the approved outcome; the lead fixes in-scope functional findings and re-reviews until none remain. Its differentiator is independence and exhaustiveness — a reviewer that fails differently from the authors, run to clean — distinct from the recursive-refinement ladder. Invoked by the team lead from the unified pre-ship gate (code-mode and /swarm:refine) after the ship steps.

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Drive a GitHub Copilot (or any bot reviewer) pull-request review to a clean pass without babysitting it: fix each finding in its own commit, reply to the review thread with the fix sha, resolve the thread, re-request the bot, and poll for the async re-review. Covers the thread node-id (PRRT_...) vs comment databaseId distinction, the resolveReviewThread GraphQL mutation, the copilot-pull-request-reviewer[bot] slug, and how to read the bot's verdict (COMMENTED plus a "human review recommended" banner is not a blocking finding). Use when Copilot has left review comments on your PR, when bot review threads must be closed out with an auditable fix-reply-resolve trail before merge, or when you need to verify that a re-review actually landed on the new HEAD rather than the old one.

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Review and resolve PR review comments on the current branch's PR in this Flutter repository, from both AI reviewers (CodeRabbit, CodiumAI, CodePilot, Copilot, etc.) and human reviewers. Fetches comments via `gh`, splits them into AI and human groups, verifies each comment against the actual Flutter code, triages them, proposes fixes, and optionally applies fixes, replies to comments, and pushes. Use when the user asks to review PR comments, resolve PR feedback, review AI comments, review human review comments, or handle code review feedback.

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Analyzes code diffs and files to identify bugs, security vulnerabilities (SQL injection, XSS, insecure deserialization), code smells, N+1 queries, naming issues, and architectural concerns, then produces a structured review report with prioritized, actionable feedback. Use when reviewing pull requests, conducting code quality audits, identifying refactoring opportunities, or checking for security issues. Invoke for PR reviews, code quality checks, refactoring suggestions, review code, code quality. Complements specialized skills (security-reviewer, test-master) by providing broad-scope review across correctness, performance, maintainability, and test coverage in a single pass.

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Run an adversarial two-phase code review of a change with TWO independent reviewers — Claude and Codex — who review alone, then cross-examine each other's findings, then Claude synthesizes a single weighted verdict. Use when the user says "/adversarial-review", "adversarial review", "review this with Codex", "get Codex to review", "two-reviewer review", "cross-examine this PR", or wants a second independent model to grade a change before merge.

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Perform a code review on {{engine_name}} {{engine_code_language}} code. Checks for bugs, security issues, performance problems, and best practices against the project's coding rules, design principles, and framework-specific conventions. Supports four modes — staged changes, a pull request, a commit range, or individual files. Use when the user says "review code", "check my code", "code review", "review PR", "review staged changes", "review these commits", or "is this code okay". Optional +check flag validates findings via a fresh-context subagent.

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Claude Code (code.claude.com) デプロイ・CI/CD リファレンス。 Amazon Bedrock / Google Cloud Agent Platform (Vertex AI) / Microsoft Foundry / Claude Platform on AWS、 Claude apps gateway、LLM gateway (protocol / rollout)、 GitHub Actions (claude-code-action) / GitLab CI/CD / GitHub Enterprise Server (GHES)、 Code Review (REVIEW.md・review level・@claude review always・コスト・トラブルシュート)、 ローカル /code-review、ultrareview (claude ultrareview)、 Slack (Claude Tag、旧 Claude Code in Slack、Pro/Max)、 headless mode、cloud environments、devcontainer、 self-hosted environments（runner 構成・identity 検証・本番デプロイ）。

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Requests a code review from a separate agent after implementation or before merging. It provides the change summary, requirements, and commit range, then guides follow-up work according to the severity of the findings.

• Reviewing a major feature after implementation
• Checking changes before merging
• Getting another perspective on a complex bug fix

Create an SVG usage card from local Claude Code, Codex, Gemini CLI, and OpenCode logs. It summarizes token counts, equivalent API cost, consecutive activity days, and each agent's share for inclusion in a README or documentation.

• Displaying coding-agent usage in a README
• Sharing an activity summary across multiple agents
• Showing token counts and equivalent API cost

Create CodeTour files that guide readers through a codebase step by step, with verified file and line references. Tailor the walkthrough to new contributors, architecture readers, PR reviewers, or investigators tracing a failure or security boundary.

• Creating onboarding walkthroughs for new maintainers
• Explaining architecture and feature execution paths
• Guiding reviewers through PR changes

Guides delegation of coding tasks to Claude Code CLI through Hermes. Covers one-shot runs and ongoing interactive sessions for feature work, bug fixes, refactoring, and reviews, with controls for tool permissions, execution limits, and structured results.

• Delegating feature implementation or bug fixes
• Reviewing code changes and pull requests
• Iterating on refactoring and tests

Delegate feature development, code refactoring, and pull request reviews to OpenAI Codex CLI. The skill also covers monitoring long tasks and fixing multiple issues in parallel using separate Git working directories.

• Adding a feature to an existing project
• Refactoring an authentication module
• Reviewing proposed code changes

Set up and use gstack in Capy or Claude Code for planning, code review, debugging, and release work. It checks the local environment, handles installation or repairs when needed, and selects the workflow instructions for the task.

• Set up gstack in a Capy environment
• Choose a workflow for planning or code review
• Check and repair an existing installation

Manage command-line tools connected to OmniRoute through its API. Inspect tool status, read or change settings, manage Codex profiles and backups, and invoke tool plugins for automation tasks.

• Reviewing settings across connected tools
• Managing Codex profiles
• Checking tool status and logs

Take a pull request through repeated code review and fixes, verify that automated checks pass for the latest commit, and combine its changes into one commit when merging. Conflicts with the request’s goal require confirmation.

• Reviewing, fixing, and merging a pull request
• Resolving every review finding, including minor issues
• Checking CI results for the commit being merged

Coordinate GitHub pull request reviews by assigning comment triage and code changes to dedicated sub-agents. Repeat the process, track decisions and progress, and reply to and resolve threads as fixes are completed.

• Work through outstanding pull request review comments
• Separate required fixes from items outside the pull request scope
• Repeat review and implementation until actionable items are cleared

Review code changes through a structured check of requirements, design, correctness, security, performance, and tests. Produce specific, constructive feedback that separates required fixes from optional suggestions, and build shared review guidelines for a development team.

• Review a pull request systematically
• Create a shared code review checklist
• Give actionable feedback to junior developers

Manage Codewhale fleet runs by inspecting workers, the agents carrying out tasks, and reviewing logs and artifacts. Classify failures, choose a supported recovery action or draft a request for human review, and summarize evidence and follow-up ownership.

• Checking workers in a Codewhale fleet run
• Assessing whether a temporary failure warrants a restart
• Resuming a run after a manager restart

Review source code for MCP, a protocol connecting AI applications to tools. Check authentication, input validation, unsafe execution, and other security risks, then report findings with file and line references and separate manual follow-ups.

• Reviewing an MCP server before release
• Checking authentication and validation on a network-exposed server
• Auditing tool code for unsafe execution paths

Review a diffusers contribution before opening a pull request. Check the full change against project rules, trace potentially unused code, and receive a severity-based report separating required fixes from points to discuss with reviewers.

• Checking a diffusers contribution before opening a pull request
• Investigating potentially unused code in a change
• Reviewing fixes again and preparing notes for reviewers

Get answers about Qwen Code usage, features, configuration, and troubleshooting from its official documentation. The skill also helps inspect and edit user or project settings files when configuration changes are requested.

• Learning Qwen Code features and commands
• Checking how to configure MCP server connections
• Reviewing or changing settings.json

Set up zvec-grep (zg) for use with Qwen Code. Check existing installation and settings, explain the integration changes, and request approval before installing the package and registering it with Qwen Code.

• Install zg and connect it to Qwen Code
• Check existing zg installation and integration settings
• Review configuration changes before installation

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.

• Reviewing changes for bugs before integration
• Investigating state mismatches across components
• Checking whether a fix introduces another defect