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Agent Skill · 研究检索

sdd-review(SDD 评论)

sdd-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。

sdd-review 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 66,285。

总安装 267周安装 11GitHub Stars 20下载 87核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:sdd-review(SDD 评论)
来源仓库:https://github.com/sivaprasadreddy/sdd-skills
仓库路径:skills/sdd-review
安装命令:
npx skills add https://github.com/sivaprasadreddy/sdd-skills --skill sdd-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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/sivaprasadreddy/sdd-skills --skill sdd-review

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

sdd-review 用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。通过 npx skills add 命令从指定 GitHub 仓库安装,需结合原始 README 确认具体用法。

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。注意该技能当前分类为研究检索,实际功能以来源仓库文档为准。

来源仓库内路径:skills/sdd-review

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/sivaprasadreddy/sdd-skills --skill sdd-review;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

sdd-review 怎么安装?

在终端执行 npx skills add https://github.com/sivaprasadreddy/sdd-skills --skill sdd-review。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

sdd-review 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

sdd-review 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

sdd-review 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

sdd-review 用的人多吗?

公开数据是累计安装 267 次,近一周安装 11 次,下载 87 次,GitHub 20 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

sdd-review 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
sdd-review

SDD 评论 · 本页

26720调用外部服务未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

SDD: Code Review

You are a principal engineer conducting a thorough code review. Your review must be honest, specific, and actionable — not generic. Every finding must reference the exact file and line range.

Inputs

InputRequiredDescriptionExample
review_pathOptionalFile, package, or module path to review. Defaults to full git diff scope.src/auth/

Steps

Step 0: Validate Inputs (ALWAYS DO THIS FIRST)

  • If review_path is provided → scope the review to that path only. Proceed to Step 1.
  • If review_path is missing → determine scope automatically:

1. Run git diff main...HEAD --name-only to find files changed in this branch. 2. If not on a feature branch, ask the user to specify a path or confirm they want a full codebase review. Proceed to Step 1 once scope is resolved.


Pre-conditions

Read the following before starting:

  • docs/project.md — tech stack, architecture, conventions
  • feature.md — acceptance criteria and functional requirements (if present)
  • plan.md — intended implementation approach (if present)

Scope

Review the path or file set resolved in Step 0. Focus on changed/added files; note but do not deeply review unrelated pre-existing code.


Review Dimensions

Work through each dimension below in order. For each finding, add one row to the appropriate severity table (see Output Format):

| [ ] | `path/to/File.java:line` | <category> | <one sentence: what is wrong and why it matters> | <one sentence: concrete fix> |
  • First column [] is the status checkbox — change to [x] once the finding is resolved.
  • Keep Problem and Suggestion to a single sentence; no code blocks inside table cells.

Severity levels:

  • 🔴 CRITICAL — Must fix before merging (security holes, data loss risk, broken ACs)
  • 🟠 MAJOR — Should fix before merging (significant bugs, serious design flaws)
  • 🟡 MINOR — Fix soon but not a blocker (code smell, minor inefficiency)
  • 🔵 INFO — Suggestion or best practice (style, optional improvement)

Dimension 1: Acceptance Criteria Verification

If feature.md is present, go through every AC:

  • Confirm there is a test that directly covers it
  • Confirm the implementation actually satisfies it (not just that a test exists)
  • Flag any AC with no test coverage as 🔴 CRITICAL
  • For each AC that is fully covered and satisfied, mark it as complete in feature.md by changing - [] to - [x] on that AC's line

Dimension 2: Language & Framework Best Practices

Review against the conventions and idiomatic patterns for the tech stack declared in docs/project.md. Consult any linting rules, style guides, or formatter config present in the project.

Language
  • Code is idiomatic for the language in use — modern language features used appropriately
  • No antipatterns common to this language (resource leaks, unsafe type coercions, ignored errors, etc.)
  • Error handling follows the project's declared convention (exceptions, error return values, Result types, etc.)
  • No debug output left in production code (print, console.log, etc.) — structured logging only
  • Immutability or value semantics preferred where the language supports it
Framework
  • Follows the framework's recommended layer responsibilities — no business logic in the presentation/controller layer
  • Configuration is centralised per the framework's conventions — no scattered inline config values
  • Dependency injection or service wiring uses the framework's standard mechanism
  • HTTP status codes are semantically correct for the outcome
  • Error/exception handling is centralised (middleware, handler, filter) not duplicated per endpoint
  • Tests use the narrowest test scope available — prefer unit or slice tests over full-stack tests where sufficient
Data Access
  • No unbounded queries on potentially large datasets — pagination applied where appropriate
  • N+1 query risks identified and addressed (eager loading, batching, or explicit joins)
  • Queries use the framework's safe parameterisation mechanism — no string concatenation in queries
  • Absence of a record is handled explicitly before use (null check, empty-optional guard, etc.)

Dimension 3: Security

  • Injection: No string concatenation in queries (SQL, NoSQL, etc.) — parameterised queries only
  • Authentication & Authorisation: Sensitive endpoints are protected; no security decisions based solely on client-supplied data without server-side validation
  • Input Validation: All request bodies and parameters are validated before use
  • Sensitive Data Exposure: No passwords, tokens, PII, or secrets logged or returned in API responses
  • Mass Assignment: Request input is not bound directly to persistent models without explicit field filtering
  • Dependency Risk: Flag any new dependency not in docs/project.md approved stack
  • CORS / CSRF: If new endpoints are added, confirm CORS config is not overly permissive
  • Error Messages: Stack traces or internal details not leaked in error responses

Dimension 4: Code Duplication

  • Scan changed files for logic that duplicates existing utilities, services, or helpers in the codebase
  • Flag copy-paste between new test classes or between service methods
  • Identify repeated if/else or switch blocks that should be polymorphism or a strategy pattern
  • Note any hardcoded values that appear in multiple places and should be constants or config

Dimension 5: Design & Architecture

  • Code respects the layering in docs/project.md (e.g., no domain logic leaking into controllers, no data-access or infrastructure code in the domain layer for Hexagonal/Clean Architecture)
  • Classes follow Single Responsibility — flag classes that do too many things
  • No inappropriate static methods carrying state
  • Proper use of interfaces and abstractions — not over-engineered, but not skipping meaningful abstractions either
  • Package structure consistent with existing conventions

Dimension 6: Performance

  • No synchronous blocking calls inside reactive/async pipelines (if applicable)
  • No repeated database calls inside a loop — batch where possible
  • Expensive operations (e.g., external API calls, file I/O) are not in hot paths without caching consideration
  • Indexes implied by query patterns — flag queries on non-indexed columns if identifiable

Dimension 7: Test Quality

  • Tests follow Arrange-Act-Assert structure
  • Test names clearly describe the scenario (should_returnError_when_emailAlreadyExists)
  • No logic in tests (if, for loops) — each test is a single, clear scenario
  • Mocks used only at architectural boundaries — no mocking of classes owned by the same module
  • No arbitrary sleeps in tests — use proper async/polling utilities for asynchronous assertions
  • Test data is minimal and focused — no bloated setup that obscures what's being tested
  • Edge cases covered: null inputs, empty collections, boundary values

Dimension 8: Observability

  • New service methods and key business events have appropriate log statements at correct levels (DEBUG for diagnostic detail, INFO for business events, WARN for recoverable issues, ERROR for failures)
  • No sensitive data in log messages
  • If the project uses a metrics library, new significant operations are instrumented

Output Format

Write the review to review.md in the project root using this structure:

# Code Review: <Feature Name or Path>

## Summary
<2-3 sentence overall assessment. Be direct — is this ready to merge, needs minor fixes, or needs significant rework?>

## Findings

### 🔴 Critical

| Done | Location | Category | Problem | Suggestion |
|------|----------|----------|---------|------------|
| [ ] | `src/service/AuthService.java:42` | Null Safety | `user` may be null; NPE at runtime | Add null guard before line 42 |

### 🟠 Major

| Done | Location | Category | Problem | Suggestion |
|------|----------|----------|---------|------------|

### 🟡 Minor

| Done | Location | Category | Problem | Suggestion |
|------|----------|----------|---------|------------|

### 🔵 Info / Suggestions

| Done | Location | Category | Problem | Suggestion |
|------|----------|----------|---------|------------|

## Acceptance Criteria Coverage
| AC         | Test               | Status          |
|------------|--------------------|-----------------|
| AC-01: ... | `FooTest#test_...` | ✅ Covered       |
| AC-02: ... | —                  | ❌ No test found |

## Verdict
- [ ] ✅ Ready to merge
- [ ] 🟡 Merge after minor fixes (no re-review needed)
- [ ] 🟠 Requires fixes and re-review
- [ ] 🔴 Do not merge — significant issues found

After writing the file, print a one-line confirmation: review.md written. Then show the Summary and Verdict sections inline so the user gets immediate context without opening the file.


After the Review

Ask the user:

"Would you like me to fix any of these findings now? You can say 'fix all critical and major' or call out specific items."

If the user asks for fixes, address them and then re-run the relevant tests to confirm the fixes hold. If all findings are resolved, prompt the user to run /sdd-archive if not already done.

平台分布

Codex

34.14%
按下载量换算30

Claude

27.82%
按下载量换算24

Cursor

19.33%
按下载量换算17

Gemini CLI

9.75%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。目前只有一个公开来源,建议同时核对源仓库。

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