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software-code-review软件代码审查

Agent Skill

software-code-review 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

2,945

周安装

118

GitHub Stars

59

下载量

953
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:software-code-review(软件代码审查)
来源仓库:https://github.com/vasilyu1983/ai-agents-public
仓库路径:skills/software-code-review
安装命令:
npx skills add https://github.com/vasilyu1983/ai-agents-public --skill software-code-review
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/vasilyu1983/ai-agents-public --skill software-code-review

简介

software-code-review 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 它可结合来源仓库、安装命令和原始 README 继续核验具体用法。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。
  • 通过 npx skills add https://github.com/vasilyu1983/ai-agents-public --skill software-code-review 安装。
  • 适用于研究检索类任务,需配合宿主环境使用。

SKILL.md

Code Reviewing Skill — Quick Reference

This skill provides operational checklists and prompts for structured code review across languages and stacks. Use it when the primary task is reviewing existing code rather than designing new systems.

Quick Reference

Review TypeFocus AreasKey ChecklistWhen to Use
Security ReviewAuth, input validation, secrets, OWASP Top 10software-security-appsecSecurity-critical code, API endpoints
Supply Chain ReviewDependencies, lockfiles, licenses, SBOM, CI policiesdev-dependency-managementDependency bumps, build/CI changes
Performance ReviewN+1 queries, algorithms, caching, hot pathsDB queries, loops, memory allocationHigh-traffic features, bottlenecks
Correctness ReviewLogic, edge cases, error handling, testsBoundary conditions, null checks, retriesBusiness logic, data transformations
Maintainability ReviewNaming, complexity, duplication, readabilityFunction length, naming clarity, DRYComplex modules, shared code
Test ReviewCoverage, edge cases, flakiness, assertionsTest quality, missing scenariosNew features, refactors
Frontend ReviewAccessibility, responsive design, performancefrontend-review.mdUI/UX changes
Backend ReviewAPI design, error handling, database patternsapi-review.mdAPI endpoints, services
Blockchain ReviewReentrancy, access control, gas optimizationcrypto-review.mdSmart contracts, DeFi protocols

Specialized:.NET/EF Core Crypto Integration

Skip unless reviewing C#/.NET crypto/fintech services using Entity Framework Core.

For C#/.NET crypto/fintech services using Entity Framework Core, see:

Key rules summary:

  • Review only new/modified code in the MR
  • Use decimal for financial values, UTC for dates
  • Follow CC-SEC-03 (no secrets in code) and CC-OBS-02 (no sensitive data in logs)
  • Async for I/O, pass CancellationToken, avoid .Result/.Wait() (see CC-ERR-04, CC-FLOW-03)
  • EF Core: AsNoTracking for reads, avoid N+1, no dynamic SQL
  • Result<T> pattern for explicit success/fail

When to Use This Skill

Invoke this skill when the user asks to:

  • Review a pull request or diff for issues
  • Audit code for security vulnerabilities or injection risks
  • Improve readability, structure, and maintainability
  • Suggest targeted refactors without changing behavior
  • Validate tests and edge-case coverage

When NOT to Use This Skill

Decision Tree: Selecting Review Mode

Code review task: [What to Focus On?]
    ├─ Security-critical changes?
    │   ├─ Auth/access control → Security Review (OWASP, auth patterns)
    │   ├─ User input handling → Input validation, XSS, SQL injection
    │   └─ Smart contracts → Blockchain Review (reentrancy, access control)
    │
    ├─ Performance concerns?
    │   ├─ Database queries → Check for N+1, missing indexes
    │   ├─ Loops/algorithms → Complexity analysis, caching
    │   └─ API response times → Profiling, lazy loading
    │
    ├─ Correctness issues?
    │   ├─ Business logic → Edge cases, error handling, tests
    │   ├─ Data transformations → Boundary conditions, null checks
    │   └─ Integration points → Retry logic, timeouts, fallbacks
    │
    ├─ Maintainability problems?
    │   ├─ Complex code → Naming, function length, duplication
    │   ├─ Hard to understand → Comments, abstractions, clarity
    │   └─ Technical debt → Refactoring suggestions
    │
    ├─ Test coverage gaps?
    │   ├─ New features → Happy path + error cases
    │   ├─ Refactors → Regression tests
    │   └─ Bug fixes → Reproduction tests
    │
    └─ Stack-specific review?
        ├─ Frontend → [frontend-review.md](assets/web-frontend/frontend-review.md)
        ├─ Backend → [api-review.md](assets/backend-api/api-review.md)
        ├─ Mobile → [mobile-review.md](assets/mobile/mobile-review.md)
        ├─ Infrastructure → [infrastructure-review.md](assets/infrastructure/infrastructure-review.md)
        └─ Blockchain → [crypto-review.md](assets/blockchain/crypto-review.md)

Multi-Mode Reviews:

For complex PRs, apply multiple review modes sequentially:

  1. Security first (P0/P1 issues)
  2. Correctness (logic, edge cases)
  3. Performance (if applicable)
  4. Maintainability (P2/P3 suggestions)

Async Review Workflows (2026)

Timezone-Friendly Reviews

PracticeImplementation
Review windowsDefine 4-hour overlap windows
Review rotationAssign reviewers across timezones
Async communicationUse PR comments, not DMs
Review SLAs24-hour initial response, 48-hour completion

Non-Blocking Reviews

PR Submitted -> Auto-checks (CI) -> Async Review -> Merge
       |              |               |
  Author continues   If green,    Reviewer comments
  on other work      queue for    when available
                     review

Anti-patterns:

  • Synchronous review meetings for routine PRs
  • Blocking on reviewer availability for non-critical changes
  • Single reviewer bottleneck

Review Prioritization Matrix

PriorityCriteriaSLA
P0Security fix, production incident4 hours
P1Bug fix, blocking dependency24 hours
P2Feature work, tech debt48 hours
P3Documentation, refactoring72 hours

Optional: AI/Automation Extensions

Note: AI-assisted review tools. Human review remains authoritative.

AI Review Assistants

ToolUse CaseLimitation
GitHub Copilot PRSummary, suggestionsMay miss context
CodeRabbitAutomated PR review commentsRequires human validation
QodoTest generation + review, 15+ workflowsEnterprise pricing
OpenAI CodexSystem-level codebase contextAPI integration required
AWS Security AgentOWASP Top 10, policy violationsPreview only (2026)
Endor Labs AI SASTAI-assisted SASTSecurity-focused
GraphitePR stacking, stack-aware merge queueProcess, not content

AI assistant rules:

  • AI suggestions are advisory only
  • Human reviewer approves/rejects
  • AI cannot bypass security review
  • AI findings require manual verification

AI Review Checklist

  • AI suggestions validated against codebase patterns
  • AI-flagged issues manually confirmed
  • False positives documented for tool improvement
  • Human reviewer explicitly approved

Simplicity and Complexity Control

  • Prefer existing, battle-tested libraries over bespoke implementations when behavior is identical.
  • Flag avoidable complexity early: remove dead/commented-out code, collapse duplication, and extract single-responsibility helpers.
  • Call out premature optimization; favor clarity and measured, evidence-based tuning.
  • Encourage incremental refactors alongside reviews to keep modules small, predictable, and aligned to standards.

Operational Playbooks

Shared Foundation

Code Review Specific

Default Review Output (Agent-Facing)

When producing a review, default to:

  • Short summary of intent + risk
  • Findings grouped by P0/P1/P2/P3 (mark REQUIRED vs OPTIONAL)
  • Concrete suggestions (minimal diffs or test cases)
  • Follow-up questions when requirements or constraints are unclear

Use assets/core/review-comment-guidelines.md for comment style and labeling.

Navigation

Resources

Templates

Data


Trend Awareness Protocol

IMPORTANT: When users ask recommendation questions about code review tools, practices, or automation, you MUST use WebSearch to check current trends before answering.

Trigger Conditions

  • "What's the best code review tool?"
  • "What should I use for [automated code review/PR automation]?"
  • "What's the latest in code review practices?"
  • "Current best practices for [code review/PR workflow]?"
  • "Is [GitHub Copilot PR/CodeRabbit] still relevant in 2026?"
  • "[CodeRabbit] vs [Graphite] vs [other]?"
  • "Best AI code review assistant?"

Required Searches

  1. Search: "code review best practices 2026"
  2. Search: "[specific tool] vs alternatives 2026"
  3. Search: "AI code review tools January 2026"
  4. Search: "PR automation trends 2026"

What to Report

After searching, provide:

  • Current landscape: What code review tools/practices are popular NOW
  • Emerging trends: New AI assistants, PR tools, or review patterns gaining traction
  • Deprecated/declining: Tools/approaches losing relevance or support
  • Recommendation: Based on fresh data, not just static knowledge

Example Topics (verify with fresh search)

  • AI code review (GitHub Copilot PR, CodeRabbit, Cursor)
  • PR automation (Graphite, Stacked PRs, merge queues)
  • Code review platforms (GitHub, GitLab, Bitbucket)
  • Review bots and automation
  • Async review practices for distributed teams
  • Review metrics and analytics tools

Fact-Checking

  • Use web search/web fetch to verify current external facts, versions, pricing, deadlines, regulations, or platform behavior before final answers.
  • Prefer primary sources; report source links and dates for volatile information.
  • If web access is unavailable, state the limitation and mark guidance as unverified.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

31.35%
按下载量换算299

Antigravity

22.86%
按下载量换算218

Cursor

19.6%
按下载量换算187

Gemini CLI

12.71%
按下载量换算121

OpenCode

7.75%
按下载量换算74

Codex

3.51%
按下载量换算33

安全审计

Gen Agent Trust Hub

通过

Socket

未通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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