“code-review”的搜索结果

通过先写失败测试、再添加最小实现来开发功能或修复缺陷。从调用方使用的公开接口验证行为，编写不依赖内部结构的测试。

• 先写测试再添加功能
• 从缺陷复现测试开始修复
• 确定集成测试覆盖的接口

以指定提交、分支或标签为基准，从开发规范和原始需求两个角度审查代码变更。分别报告规范问题与需求缺漏，便于独立判断两方面的结果。

• 审查分支或PR的变更
• 检查指定提交或标签之后的变更
• 对照已记录的开发规范

读取规格说明和相关工单的依赖关系，安排多个代理推进实现。经过测试、代码审查和问题修正后，将成果汇总到一个集成分支，并完成工单处理。

• 实现分散在多个工单中的需求
• 并行实现相互独立的任务
• 将成果汇总到集成分支

依据项目所用状态管理库的惯例审查Flutter/Dart代码，从界面结构、异步操作到性能、测试、无障碍和安全性，帮助发现应用中的问题。

• 发布前审查Flutter应用
• 检查状态管理设计
• 排查不必要的界面重建

帮助实现和检查React、Next.js表单与模态框的键盘操作及屏幕阅读器支持，改进标签、错误提示和焦点移动。

• 改进表单标签与错误提示
• 检查下拉菜单的键盘操作
• 管理模态框开关时的焦点

在提交代码前检查差异，依次执行安全扫描、测试、静态检查和独立智能体审查；比较修改前后的失败情况，并由另一智能体仅修复已指出的问题。

• 提交前检查新增功能
• 检查新增代码中的机密信息和攻击风险
• 区分新增与既有的测试失败

审查 Spec Kit 的代码差异和拉取请求，核对设计文档、预期与异常行为测试、缺陷修复的回归测试证据，以及仓库术语的一致性。

• 审查 Spec Kit 拉取请求
• 检查预期与异常行为的测试
• 核对缺陷修复的回归测试

在合并前从正确性、可读性、架构、安全和性能五个维度审查代码变更，检查测试是否恰当，区分必须修复的问题与可选建议，并提出具体改进方法。

• 合并前审查拉取请求
• 检查人工智能编写的代码
• 评估重构是否带来改善

将已完成的改动整理为GitHub拉取请求，处理分支与提交、撰写说明和验证记录、附上界面变化证据，并回复审核意见。

• 将完成的改动整理为GitHub PR
• 记录验证结果与界面变化
• 回复审核意见并提交修正

按变更规模、自动检查结果、冲突及停滞情况整理GitHub待处理的拉取请求，明确审查优先级；可深入审查选定请求，起草评论并在用户批准后发布。

• 确定待处理拉取请求的审查顺序
• 检查变更重叠和自动检查失败
• 深入审查指定的拉取请求

从安全性、正确性、性能、可维护性和测试质量检查代码，整理问题位置、影响、修复建议、改进项与已有优点，并给出是否适合合并的判断。

• 合并前审查代码变更
• 检查缺陷和边界条件
• 排查漏洞及依赖问题

使用多个专业AI代理审查GitHub代码变更提案，整理安全、性能、设计、格式和无障碍问题，并可提出修复建议、发布审查结果。

• 检查身份验证变更的安全性
• 检查数据库变更的性能影响
• 审查界面易用性和格式

Review code changes in a diff, pull request, branch, or file path to identify bugs and cleanup opportunities. Findings include file locations and concrete failure scenarios, with options to apply fixes or post comments.

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• Review uncommitted changes for bugs
• Check a pull request or branch before merging
• Find duplicated logic and unnecessary work

Coordinate large migrations, refactors, and bulk renames by splitting them into independent tasks. After plan approval, 5–30 agents work in separate Git worktrees, isolated working directories, then review, test, and open a pull request for each task.

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• Migrate code across many files
• Refactor independent modules in parallel
• Rename identifiers across directories

Plan and write tests for changes to agent behavior, favoring integration tests that check components together. Identify key logic changes and user-visible behavior to cover, reuse existing helpers, and keep unit tests in dedicated files.

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• Identify test coverage for changes to agent logic
• Add integration tests for user-visible behavior
• Organize unit tests in dedicated files

Assess whether a code change is small enough to review using line-count guidance. For larger changes, examine the actual differences, dependencies, and calling code to suggest reviewable stages and the smallest coherent first step.

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• Check the size of a change before requesting review
• Assess the scope of a complex logic change
• Plan reviewable stages for a large change

Review code that manages the conversation history and extra information sent to Codex models. Apply rules for incremental history, size limits, cache stability, manual review of large additions, and required implementation structures.

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• Review changes to conversation history handling
• Check size limits on information sent to the model
• Identify large additions requiring manual review

Review code changes with several independent reviewers working in parallel, then receive organized findings. Request a quick or thorough review, choose to hand off fixes, or run without interaction when another workflow or CI job initiates the review.

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• Review code changes from multiple independent perspectives
• Choose a quick or thorough review
• Receive findings with fixes handed off

Review changed code against project rules and report missing tests, unused code, typing problems, and style violations. It also checks API design and data isolation, helping developers identify issues after implementation.

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• Reviewing changes after implementation
• Finding missing tests and unused code
• Checking Python types and API design

Guide AI coding work toward simple implementations, focused edits, and explicit assumptions. Use it when writing, reviewing, or refactoring code to keep changes tied to the request and define success through tests or other concrete checks.

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• Keeping bug fixes limited to the necessary code
• Simplifying code that has become overcomplicated
• Making implementation assumptions explicit

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.

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• Reviewing a pull request
• Checking authentication and sensitive data handling
• Finding inefficient algorithms or database queries

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.

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• Reviewing a pull request before merging
• Checking code for security risks
• Finding performance improvement opportunities

Review code for security, performance, quality, and ease of maintenance. Get an overall assessment and prioritized findings with file locations, severity, explanations of impact, and example fixes to guide improvements or Pull Request reviews.

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• Reviewing a Pull Request before merging
• Checking authentication and data exposure risks
• Finding inefficient queries and processing

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.

中文简介正在准备中。当前显示英语简介。

• Reviewing a pull request
• Checking authentication and sensitive data handling
• Finding inefficient algorithms or database queries