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Agent Skill · 研究检索

review-skills(复习技巧)

review-skills 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。

review-skills 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,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 41,143。

总安装 1,212周安装 50GitHub Stars 73下载 396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:review-skills(复习技巧)
来源仓库:https://github.com/base44/skills
仓库路径:skills/review-skills
安装命令:
npx skills add https://github.com/base44/skills --skill review-skills
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/base44/skills --skill review-skills

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。

review-skills 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词快速定位候选结果时使用。它适用于技能库管理、能力分析和线索筛选等研究检索类任务场景。通过关键词、任务场景或来源线索调用,可结合仓库 README 核验具体用法。

安装前建议确认权限范围和维护状态,注意是否会触发联网或文件读写操作。可通过 npx skills add 命令从指定 GitHub 仓库安装使用。

来源仓库内路径:skills/review-skills

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/base44/skills --skill review-skills;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

review-skills 怎么安装?

在终端执行 npx skills add https://github.com/base44/skills --skill review-skills。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

review-skills 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。

review-skills 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。

review-skills 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。

review-skills 用的人多吗?

公开数据是累计安装 1,212 次,近一周安装 50 次,下载 396 次,GitHub 73 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。

review-skills 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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。

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。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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
review-skills

复习技巧 · 本页

1,21273调用外部服务未明确未通过

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

Review Skills

Review and analyze a skill against best practices for length, intent scope, and trigger patterns.

Prerequisites

Before analyzing, read these resources to understand skill writing principles:

  1. ./references/skill-creator/SKILL.md - Core principles, anatomy, and progressive disclosure
  2. references/spec.md - Complete Agent Skills specification (required for compliance checks)
  3. references/validate.md - Validation checklist (used in Step 2)
  4. ./references/skill-creator/references/workflows.md - Workflow patterns (if relevant)
  5. ./references/skill-creator/references/output-patterns.md - Output patterns (if relevant)

Reference Examples from Anthropic (REQUIRED)

You MUST read reference skills from Anthropic's repository before analyzing. This is essential for calibrating your review.

  1. Ensure cache is available: Check if ./.cache/anthropics-skills/ exists. If not (or if stale), run: python scripts/download_anthropics_skills.py
  2. Read at least 3 reference skills: Before analyzing, read these SKILL.md files from ./.cache/anthropics-skills/skills/: Always read these high-quality examples: Then read 1-2 skills similar to the one being reviewed:

- pdf/SKILL.md - Well-structured workflow skill with clear triggers - docx/SKILL.md - Good example of document processing patterns - skill-creator/SKILL.md - Meta-skill showing best practices - For workflow-based skills: xlsx/SKILL.md, pptx/SKILL.md - For tool/API skills: mcp-builder/SKILL.md - For creative/design skills: brand-guidelines/SKILL.md, frontend-design/SKILL.md - For testing skills: webapp-testing/SKILL.md

  1. Note patterns to compare: As you read, note:

- How descriptions are structured (trigger patterns) - Length and depth of SKILL.md body - How references are organized and used - Balance between brevity and completeness

Steps

Step 1: Receive the Skill to Review

The user must provide a skill folder/path to review. If not provided, prompt:

"Please provide the path to the skill folder you want to review (e.g., .claude/skills/my-skill/)"

Step 2: Validate Skill Structure

Using the validation checklist (references/validate.md), verify the skill passes all basic checks:

  1. File Structure: SKILL.md exists
  2. Frontmatter Format: Valid YAML between --- delimiters
  3. Allowed Properties: Only name, description, license, compatibility, metadata, allowed-tools
  4. Name Validation:

- Hyphen-case only (lowercase, digits, hyphens) - No start/end hyphens, no consecutive hyphens (--) - Max 64 characters - Matches directory name

  1. Description Validation:

- No angle brackets (< or >) - Max 1024 characters - Non-empty

If validation fails: Stop the review and report the specific validation error(s). The skill must pass basic validation before proceeding with the full review.

Step 3: Read the Skill

Read the complete skill structure:

  • SKILL.md (frontmatter and body)
  • Any files in references/, scripts/, assets/ directories

IMPORTANT: Only analyze the skill provided by the user.

Step 4: Verify Spec Compliance

Check that the skill follows the Agent Skills specification (references/spec.md). Verify:

Directory Structure
  • Skill is in a directory matching the name field
  • Contains required SKILL.md file
  • Optional directories follow conventions: scripts/, references/, assets/
Frontmatter Compliance
FieldCheck
name1-64 chars, lowercase alphanumeric + hyphens, no start/end hyphens, no --, matches directory name
description1-1024 chars, non-empty, describes what and when
licenseIf present, short (license name or file reference)
compatibilityIf present, max 500 chars
metadataIf present, string keys to string values
allowed-toolsIf present, space-delimited tool list
Body Content
  • Markdown format after frontmatter
  • Recommended: step-by-step instructions, examples, edge cases
  • Under 500 lines (move detailed content to references)
Progressive Disclosure
  • Metadata (~100 tokens): name + description loaded at startup
  • Instructions (<5000 tokens recommended): SKILL.md body loaded on activation
  • Resources (as needed): scripts/references/assets loaded on demand
File References
  • Use relative paths from skill root
  • Keep references one level deep (avoid deeply nested chains)

If spec violations found: Document them clearly in the review output with specific fixes.

Step 5: Analyze the Skill

Perform analysis in four areas, comparing against the reference skills you read from Anthropic's repository:

A. Length Analysis

Using the progressive disclosure guidelines from skill-creator, evaluate:

  • Word count in description field
  • Line/word count in SKILL.md body
  • Number and size of reference files
  • Duplication between SKILL.md and reference files
B. Intent Scope Analysis

Evaluate:

  • All intents the skill serves
  • Whether skill handles multiple distinct use cases
  • Whether splitting would improve triggering accuracy
  • Trade-offs: context efficiency vs. maintenance overhead

Questions to answer:

  • Does this skill try to do too much?
  • Are there distinct user intents that deserve separate skills?
C. Trigger Analysis (CRITICAL)

The description field is the primary triggering mechanism. Evaluate it for three types of triggers:

Trigger TypeWhat to Check
User INTENTDoes it describe what the user wants to do? (e.g., "deploy", "create", "edit")
TECHNICAL contextDoes it mention code patterns, file types, imports? (e.g., "base44.entities.*", ".jsonc files")
Project stackDoes it mention frameworks, tools, file structures? (e.g., "Vite", "Next.js", "base44/")

Check:

  • Does description cover both intent-based AND technical triggers?
  • Is it specific enough to trigger correctly, but broad enough to not miss cases?
  • Are there gaps where the skill might not trigger when it should?
  • Does it clearly distinguish from similar skills?

Good trigger pattern example:

ACTIVATE when (1) INTENT - user wants to [action]; (2) TECHNICAL - code contains [patterns], uses [APIs]; (3) CONTEXT - project has [structure/files]

Step 6: Provide Recommendations

Summarize findings with actionable recommendations for:

  1. Spec Compliance: What needs to be fixed to follow the spec?
  2. Length: What should be trimmed or split?
  3. Intent Scope: Should it be split or combined?
  4. Triggers: How can the description be improved?

Output Format

## Skill Review: [Skill Name]

### Reference Skills Compared
- [List the 3-5 Anthropic skills you read before this review]

### Summary
[1-2 sentence overview]

### Validation Result
- **Status**: [Pass/Fail]
- **Details**: [Validation output or errors]

### Spec Compliance
- Directory structure: [Pass/Fail - details]
- Frontmatter fields: [Pass/Fail - details]
- Body content: [Pass/Recommendations]
- Progressive disclosure: [Pass/Recommendations]
- File references: [Pass/Recommendations]
- **Assessment**: [Compliant/Partially compliant/Non-compliant]
- **Fixes Required**: [List of specific fixes if any]

### Length Analysis
- Description: X words
- SKILL.md body: X lines / X words
- Reference files: X files
- **Assessment**: [Pass/Needs attention]
- **Recommendations**: [Specific suggestions]

### Intent Scope Analysis
- Intents served: [List]
- **Assessment**: [Focused/Broad/Too broad]
- **Recommendations**: [Split suggestions if applicable]

### Trigger Analysis
- Intent coverage: [Yes/Partial/No]
- Technical coverage: [Yes/Partial/No]
- Stack coverage: [Yes/Partial/No]
- **Assessment**: [Strong/Adequate/Weak]
- **Recommendations**: [Specific description improvements]

### Overall Recommendations
1. [Priority 1 action item - spec compliance fixes if any]
2. [Priority 2 action item]
3. [Priority 3 action item]
4. [Priority 4 action item]

平台分布

Codex

35.5%
按下载量换算141

Claude

29.31%
按下载量换算116

Cursor

16.52%
按下载量换算65

Gemini CLI

9.36%
按下载量换算37

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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