Token导航 LogoToken导航TokenDH.com
研究检索需要联网github未标认证来源可访问许可证需确认审计通过

leverage-point-audit杠杆点审计

Agent Skill

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

总安装

264

周安装

11

GitHub Stars

61

下载量

88
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:leverage-point-audit(杠杆点审计)
来源仓库:https://github.com/melodic-software/claude-code-plugins
仓库路径:skills/leverage-point-audit
安装命令:
npx skills add https://github.com/melodic-software/claude-code-plugins --skill leverage-point-audit
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/melodic-software/claude-code-plugins --skill leverage-point-audit

简介

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。

  • 适用于系统安全评估、权限架构审查和漏洞排查等安全运维场景。
  • 使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。
  • 建议结合业务上下文进行二次验证,避免将模拟数据误判为真实风险点。
  • leverage-point-audit 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Leverage Point Audit

Audit a codebase against the 12 leverage points framework to identify gaps and improve agentic coding success.

When to Use

  • Before starting a new agentic coding project
  • When agents are failing or requiring many attempts
  • When KPIs (Size, Attempts, Streak, Presence) are not improving
  • For periodic health checks of agentic capability

The 12 Leverage Points

In-Agent (Core Four)

  1. Context - CLAUDE.md, README, project docs
  2. Model - Appropriate model selection
  3. Prompt - Clear instructions and templates
  4. Tools - Required capabilities available

Through-Agent (External)

  1. Standard Out - Logging for visibility
  2. Types - Information Dense Keywords (IDKs)
  3. Documentation - Agent-specific context
  4. Tests - Self-correction capability (HIGHEST LEVERAGE)
  5. Architecture - Navigable codebase structure
  6. Plans - Meta-work communication
  7. Templates - Reusable prompts (slash commands)
  8. ADWs - Autonomous workflows

Audit Workflow

Step 1: Check Context (Leverage Points 1-4)

CLAUDE.md presence:

Search for: CLAUDE.md, .claude/CLAUDE.md
Check: Does it explain the project? Conventions? Common commands?

README.md quality:

Search for: README.md
Check: Does it explain structure? How to run? How to test?

Permissions configuration:

Search for: .claude/settings.json
Check: Are required tools allowed?

Step 2: Check Visibility (Leverage Point 5)

Standard out patterns:

Search for: print(, console.log(, logger., logging.
Check: Are success AND error cases logged?
Check: Can agent see what's happening?

Anti-pattern detection:

Look for: Silent returns, bare except blocks, empty catch blocks
These prevent agent visibility.

Step 3: Check Searchability (Leverage Point 6)

Type definitions:

Search for: interface, type, class, BaseModel, dataclass
Check: Are names information-dense? (Good: UserAuthToken, Bad: Data)

Step 4: Check Documentation (Leverage Point 7)

Internal docs:

Search for: *.md files, docstrings, comments
Check: Do they explain WHY, not just WHAT?

Step 5: Check Validation (Leverage Point 8) - HIGHEST PRIORITY

Test presence:

Search for: test_*.py, *.test.ts, *.spec.ts, *_test.go
Check: Do tests exist? Are they comprehensive?

Test commands:

Check: Is there a simple test command? (npm test, pytest, etc.)
Check: Do tests run quickly?

Step 6: Check Architecture (Leverage Point 9)

Entry points:

Check: Are entry points obvious? (main.py, index.ts, server.py)

File organization:

Check: Consistent structure? Related files grouped?
Check: File sizes reasonable? (< 1000 lines)

Step 7: Check Templates (Leverage Point 11)

Slash commands:

Search for: .claude/commands/
Check: Are common workflows automated?

Step 8: Check ADWs (Leverage Point 12)

Automation:

Search for: GitHub Actions, hooks, triggers
Check: Are workflows automated?

Output Format

After audit, provide:

Summary Table

Leverage PointStatusPriorityRecommendation
ContextGood/Fair/PoorHigh/Med/LowSpecific action
............

Priority Actions

List top 3-5 improvements in order of impact:

  1. [Highest Impact] - Specific recommendation
  2. [High Impact] - Specific recommendation
  3. [Medium Impact] - Specific recommendation

Detailed Findings

For each leverage point:

  • Current state
  • Specific gaps found
  • Recommended improvements
  • Example of what good looks like

Example Audit Output

## Leverage Point Audit Results

### Summary
- Tests: POOR (no test files found) - HIGHEST PRIORITY
- Standard Out: FAIR (some logging, missing error cases)
- Architecture: GOOD (clear structure, reasonable file sizes)

### Priority Actions
1. Add test suite - enables self-correction
2. Add error logging to API endpoints - enables visibility
3. Create /prime command - enables quick context

### Detailed Findings
[... specific recommendations ...]

Related Memory Files

  • @12-leverage-points.md - Complete framework reference
  • @agentic-kpis.md - How to measure improvement
  • @agent-perspective-checklist.md - Quick pre-task checklist

Version History

  • v1.0.0 (2025-12-26): Initial release

Last Updated

Date: 2025-12-26 Model: claude-opus-4-5-20251101

适合场景

01

研究助手

02

事实核查

03

知识库问答

04

带来源的搜索总结

能力概览

能力 1

组合搜索和大模型调用

能力 2

支持多来源检索和总结

能力 3

强调引用来源和事实核查

能力 4

适合研究型 Agent 流程

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

33.82%
按下载量换算30

Claude

29.93%
按下载量换算26

Cursor

18.86%
按下载量换算17

Gemini CLI

9.13%
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

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。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

继续浏览同类 Skills