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Agent Skill · 研究检索

ln-160-docs-skill-extractor(ln 160 文档技能提取器)

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

ln-160-docs-skill-extractor 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,权限为执行命令;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 32,311。

总安装 2,545周安装 105GitHub Stars 441下载 832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:ln-160-docs-skill-extractor(ln 160 文档技能提取器)
来源仓库:https://github.com/levnikolaevich/claude-code-skills
仓库路径:skills/ln-160-docs-skill-extractor
安装命令:
npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-160-docs-skill-extractor
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/levnikolaevich/claude-code-skills --skill ln-160-docs-skill-extractor

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。

用于辅助文档和 Markdown 内容的整理与改写。适合提炼结构、补齐章节、统一术语或检查链接有效性。使用时应保留项目已有事实和路径, 不要把未确认信息写成确定结论;ln-160-docs-skill-extractor 属于研究检索类 Skill,可作为该场景下的辅助能力补充。涉及对外文案时需避免过度营销。

来源仓库内路径:skills/ln-160-docs-skill-extractor

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/levnikolaevich/claude-code-skills --skill ln-1…;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

    它需要执行命令,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

ln-160-docs-skill-extractor 怎么安装?

在终端执行 npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-160-docs-sk…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ln-160-docs-skill-extractor 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。

ln-160-docs-skill-extractor 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-160-docs-skill-extractor 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

ln-160-docs-skill-extractor 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。

ln-160-docs-skill-extractor 用的人多吗?

公开数据是累计安装 2,545 次,近一周安装 105 次,下载 832 次,GitHub 441 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。

ln-160-docs-skill-extractor 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 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

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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
ln-160-docs-skill-extractor

ln 160 文档技能提取器 · 本页

2,545441执行命令未明确有提醒

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

Paths: File paths (shared/, references/, ../ln-*) are relative to skills repo root. If not found at CWD, locate this SKILL.md directory and go up one level for repo root. If shared/ is missing, fetch files via WebFetch from https://raw.githubusercontent.com/levnikolaevich/claude-code-skills/master/skills/{path}.

ln-160-docs-skill-extractor

Type: L2 Coordinator Category: 1XX Documentation Pipeline Workers: ln-161-skill-creator, ln-162-skill-reviewer

Scans project documentation, identifies procedural content, and extracts it into executable slash command files under .claude/commands/*.md. Declarative documentation stays in markdown; this skill only routes procedural sections into command form.


Overview

AspectDetails
InputProject docs, test docs, and optional doc registry
Output.claude/commands/*.md files in target project
Workersln-161 creates commands, ln-162 reviews them
Source policyDocs-first extraction; AGENTS.md and CLAUDE.md are routing-only

Workflow

Phase 1: Discovery (route docs, build inventory)
    |
Phase 2: Classification (procedural vs declarative scoring)
    |
Phase 3: Extraction Plan (user approval)
    |
Phase 4: Delegate -> ln-161 (create commands)
    |
Phase 5: Delegate -> ln-162 (review commands)
    |
Phase 6: Report (aggregate results)

Phase 1: Discovery

MANDATORY READ: Load shared/references/procedural_extraction_rules.md, shared/references/markdown_read_protocol.md, and shared/references/docs_quality_contract.md

Build a docs-first inventory before extracting anything.

Routing Sources

Use these files only to route discovery and prioritize reading:

  • AGENTS.md
  • CLAUDE.md
  • docs/project/.context/doc_registry.json if present

Do not extract commands from routing sources.

Extraction Sources

Scan only these sources for procedural content:

  • docs/**/*.md
  • tests/README.md
  • tests/manual/**/*
  • README.md
  • CONTRIBUTING.md

Also scan:

  • .claude/commands/*.md to avoid duplicate command creation

Discovery Rules

  1. If docs/project/.context/doc_registry.json exists, prioritize:

- canonical docs first - DOC_KIND=how-to before reference - reference before index and explanation

  1. Read markdown with the shared section-first protocol:

- use outline first for large or unfamiliar files - read header markers and top sections first - expand only sections that might contain procedures

  1. Ignore standard doc shell sections as extraction candidates:

- Quick Navigation - Agent Entry - Maintenance - header markers such as SCOPE, DOC_KIND, DOC_ROLE, READ_WHEN, SKIP_WHEN, PRIMARY_SOURCES

Build contextStore

contextStore:
  project_root: {CWD}
  routing_sources:
    agents_md: true
    claude_md: true
    doc_registry: true
  existing_commands: [list of .claude/commands/*.md filenames]
  doc_inventory:
    - file: docs/project/runbook.md
      doc_kind: how-to
      doc_role: canonical
      sections:
        - header: "Deployment"
          line_range: [45, 92]
          signals: { code_blocks: 3, numbered_steps: 5, imperative_verbs: 8 }

Phase 2: Classification

Score each candidate section with the shared procedural extraction rules.

ClassificationConditionAction
PROCEDURALproc >= 4 and proc > decl * 2Extract to command
DECLARATIVEdecl >= 4 and decl > proc * 2Keep as documentation
MIXEDBoth >= 3Extract procedural subsection only
THINBoth < 3Skip

Filter:

  • drop sections already covered by an existing .claude/commands/*.md
  • drop standard doc shell sections
  • prefer DOC_KIND=how-to when multiple sections overlap semantically

Phase 3: Extraction Plan (User Approval Gate)

Present the classified result set to the user before creating files.

Found {N} procedural sections in {M} files:

| # | Source | DOC_KIND | Section | Score | Proposed Command |
|---|--------|----------|---------|-------|------------------|
| 1 | runbook.md | how-to | Deployment | P:8/D:1 | deploy.md |
| 2 | tests/README.md | index | Running Tests | P:7/D:2 | run-tests.md |

Existing .claude/commands/ (will skip): refresh_context.md, build-and-test.md

Include? (e.g., "1,2" or "all" or "all skip 2")

If the user approves nothing, stop with No skills to create.


Phase 4: Delegate to ln-161 (Skill Creation)

Pass only approved sections to ln-161-skill-creator.

Agent(
  description: "Create commands from procedural docs",
  prompt: "Execute skill creator.\nStep 1: Invoke:\n  Skill(skill: \"ln-161-skill-creator\")\nCONTEXT:\n{approved_sections}",
  subagent_type: "general-purpose"
)

Normalized payload:

{
  "approved_sections": [
    {
      "source_file": "docs/project/runbook.md",
      "section_header": "Deployment",
      "line_range": [45, 92],
      "command_name": "deploy.md",
      "doc_kind": "how-to",
      "doc_role": "canonical"
    }
  ]
}

Collect:

  • created file paths
  • source-to-command mapping
  • per-command summary

Phase 5: Delegate to ln-162 (Skill Review)

Pass created command paths to ln-162-skill-reviewer in COMMAND mode.

Agent(
  description: "Review created commands",
  prompt: "Execute skill reviewer in COMMAND mode.\nStep 1: Invoke:\n  Skill(skill: \"ln-162-skill-reviewer\", args: \"commands\")\nFILES: {list of created paths}",
  subagent_type: "general-purpose"
)

Collect:

  • verdict per file
  • aggregate pass/fix/warn counts

Phase 6: Report

Aggregate the create and review results.

## Docs Skill Extractor -- Complete

| Metric | Count |
|--------|-------|
| Documents scanned | {N} |
| Sections analyzed | {N} |
| Procedural found | {N} |
| Commands created | {N} |
| Commands skipped (existing) | {N} |
| Review PASS | {N} |
| Review FIXED | {N} |
| Review WARN | {N} |

Created commands:
- .claude/commands/deploy.md (from runbook.md#Deployment)
- .claude/commands/run-tests.md (from tests/README.md#Running Tests)

Critical Rules

  • Docs-first extraction: Extract only from docs sources. AGENTS.md and CLAUDE.md route discovery but never become command sources.
  • Section-first reading: Use the shared markdown read protocol before full-file reads.
  • Detect before extract: Only extract sections classified as procedural.
  • No duplicates: Skip sections already covered by existing .claude/commands/*.md.
  • User approval required: Never create commands without Phase 3 confirmation.
  • Delegate creation: All command file writing goes through ln-161.
  • Delegate review: All command validation goes through ln-162.
  • Preserve docs: Source documentation stays intact.

TodoWrite format (mandatory):

- Build docs inventory (in_progress)
- Invoke ln-161-skill-creator (pending)
- Invoke ln-162-skill-reviewer (pending)
- Aggregate report (pending)

Worker Invocation (MANDATORY)

PhaseWorkerContext
4ln-161-skill-creatorApproved procedural sections with source metadata
5ln-162-skill-reviewerCreated command file paths in COMMAND mode

All workers: Invoke via Skill tool. Workers consume only the context they need.

Definition of Done

  • Routing sources checked (AGENTS.md, CLAUDE.md, doc registry if present)
  • Extraction inventory built from docs-first sources
  • Every candidate section classified
  • User approved extraction plan
  • ln-161 created all approved commands
  • ln-162 reviewed all created commands
  • Final report aggregated with scan, create, and review metrics

Meta-Analysis

MANDATORY READ: Load shared/references/meta_analysis_protocol.md

Skill type: planning-coordinator. Run after Phase 6 completes. Output to chat using the planning-coordinator format.


Version: 1.0.0 Last Updated: 2026-03-26

平台分布

Codex

35.62%
按下载量换算296

Claude

29.63%
按下载量换算247

Cursor

19.39%
按下载量换算161

Gemini CLI

10.43%
按下载量换算87

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-160-docs-skill-extractor 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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