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review-skills复习技巧

Agent Skill

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。

总安装

1,212

周安装

50

GitHub Stars

73

下载量

396
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

2

许可证

unknown

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: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

简介

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。

SKILL.md

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]

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

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

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

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

external-service

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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