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Agent Skill · 研究检索

ln-612-semantic-content-auditor(ln 612 语义内容审核员)

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-612-semantic-content-auditor 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,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 25,066。

总安装 3,856周安装 156GitHub Stars 441下载 1,211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-612-semantic-content-auditor(ln 612 语义内容审核员)
来源仓库:https://github.com/levnikolaevich/claude-code-skills
仓库路径:skills/ln-612-semantic-content-auditor
安装命令:
npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-612-semantic-content-auditor
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-612-semantic-content-auditor

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。

用于文档、README 和内容稿件的整理与改写,适合提炼结构和统一术语。适用于需要补齐章节、检查链接或把零散材料整理成可读文档的场景。使用时保留项目已有事实、命令和路径,不把未确认信息写成确定结论。涉及对外文案时需控制语气,避免过度营销或夸大能力。安装前建议确认权限范围和维护状态,确保不会触发不必要的网络或文件操作。

来源仓库内路径:skills/ln-612-semantic-content-auditor

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-6…;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

ln-612-semantic-content-auditor 怎么安装?

在终端执行 npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-612-semanti…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ln-612-semantic-content-auditor 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-612-semantic-content-auditor 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。

ln-612-semantic-content-auditor 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-612-semantic-content-auditor 用的人多吗?

公开数据是累计安装 3,856 次,近一周安装 156 次,下载 1,211 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-612-semantic-content-auditor 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

  • 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
ln-612-semantic-content-auditor

ln 612 语义内容审核员 · 本页

3,856441调用外部服务未明确有提醒

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}.

Semantic Content Auditor (L3 Worker)

Type: L3 Worker

Specialized worker auditing semantic fitness of project documentation.

Purpose & Scope

  • Verify document content matches stated SCOPE and declared document kind
  • Check content aligns with project goals (value contribution)
  • Return structured findings to coordinator with severity, location, fix suggestions
  • Does NOT verify facts against codebase

Target Documents

Called ONLY for project documents (not reference/tasks):

DocumentVerification Focus
AGENTS.md / CLAUDE.mdEntry instructions stay scoped, navigable, and free of off-topic content
docs/README.mdNavigation scope correct, descriptions relevant
docs/documentation_standards.mdStandards applicable to this project type
docs/principles.mdPrinciples relevant to project architecture
docs/project/requirements.mdRequirements scope complete, no stale items
docs/project/architecture.mdArchitecture scope covers all layers
docs/project/tech_stack.mdStack scope matches project reality
docs/project/api_spec.mdAPI scope covers all endpoint groups
docs/project/database_schema.mdSchema scope covers all entities
docs/project/design_guidelines.mdDesign scope covers active components
docs/project/infrastructure.mdInfrastructure scope covers all deployment targets
docs/project/runbook.mdRunbook scope covers setup + operations

Excluded: docs/tasks/, docs/reference/, docs/presentation/, tests/

Inputs

MANDATORY READ: Load shared/references/audit_worker_core_contract.md, shared/references/docs_quality_contract.md, and shared/references/markdown_read_protocol.md. MANDATORY READ: Load shared/references/mcp_tool_preferences.md and shared/references/mcp_integration_patterns.md

Receives from coordinator per invocation:

FieldDescription
doc_pathPath to document to audit (e.g., docs/project/architecture.md)
output_dirDirectory for report output (from contextStore)
project_rootProject root path
tech_stackDetected technology stack

hex-line is optional for this doc-only worker. Use it to outline large markdown files when available; otherwise continue with built-in Read/Grep/Glob/Bash and do not block on MCP availability.

Workflow

Phase 1: Header and Contract Extraction

  1. Read document header and top sections first
  2. Parse:

- SCOPE - DOC_KIND - DOC_ROLE - READ_WHEN - SKIP_WHEN - PRIMARY_SOURCES

  1. If no SCOPE tag, infer from document type
  2. Infer expected DOC_KIND from the shared contract when missing
  3. Record stated purpose and routing boundaries

Phase 2: Doc-Kind-Aware Semantic Audit

Judge the document according to its kind:

DOC_KINDMain semantic question
indexDoes it route efficiently and avoid deep factual overload?
referenceIs it precise, complete enough, and easy to lookup?
how-toIs the procedure actionable and sequenced correctly?
explanationDoes it build the right mental model and rationale?
recordDoes it preserve the decision trace and consequences?

Analyze the document against stated scope and kind:

CheckFinding Type
Section not serving scopeOFF_TOPIC
Scope aspect not coveredMISSING_COVERAGE
Excessive detail beyond scopeSCOPE_CREEP
Content duplicated elsewhereSSOT_VIOLATION

Agent instruction file checks (applies when the audited file is AGENTS.md or CLAUDE.md):

CheckFinding TypeSeverityRecommendation
Style / formatting rules (indentation, quote style, trailing whitespace, naming conventions)NOT_A_LINTERWARNMove to Biome, Prettier, Ruff, EditorConfig, or a Claude Code Stop hook. Instruction files are loaded into every session and cost tokens against the ~100-imperative budget; deterministic tools do this for free.
Conditional / non-universal rules at the root (when working on src/api/..., if modifying the billing service, for the Z service)NON_UNIVERSAL_RULEWARNMove to .claude/rules/*.md with a paths: frontmatter filter (Anthropic built-in path scoping). Non-universal rules bias Claude Code toward ignoring the entire file via the <system-reminder> wrapper.
Self-Improvement Loop rule pointing at a manual tasks/lessons.mdOBSOLETE_PATTERNWARNDelete. Claude Code's built-in auto memory at ~/.claude/projects/<project>/memory/ already does this; a parallel hand-maintained convention wastes context.

All three WARN only — they require human judgment (intentional style rule? conditional scope that's actually project-wide?). Cite shared/references/agent_instructions_writing_guide.md in every finding.

Read strategy:

  • header + top sections first
  • read only the body sections needed for judgment
  • read the full file only when the semantic judgment is unsafe without it

Scoring:

  • 10/10: All content serves scope, scope fully covered
  • 8-9/10: Minor off-topic content or small gaps
  • 6-7/10: Some sections not aligned, partial coverage
  • 4-5/10: Significant misalignment, major gaps
  • 1-3/10: Document does not serve its stated purpose

Phase 3: SCORING & REPORT

Calculate final score based on scope alignment:

overall_score = weighted_average(coverage, relevance, focus)

Coverage: how completely the scope is addressed. Relevance: how much content serves the scope. Focus: absence of off-topic content.

Scoring Algorithm

MANDATORY READ: Load shared/references/audit_worker_core_contract.md and shared/references/audit_scoring.md.

Output Format

MANDATORY READ: Load shared/references/audit_worker_core_contract.md and shared/templates/audit_worker_report_template.md.

Write JSON summary per shared/references/audit_summary_contract.md. In managed mode the caller passes both runId and summaryArtifactPath; in standalone mode the worker generates its own run-scoped artifact path per shared contract.

Write report to {output_dir}/ln-612--{doc-slug}.md where doc-slug is derived from document filename (e.g., architecture, tech_stack, agents_md).

With category: "Semantic Content" and checks: scope_alignment, not_a_linter, non_universal_rule, obsolete_pattern (the last three fire only on AGENTS.md / CLAUDE.md targets).

Return summary per shared/references/audit_summary_contract.md.

When summaryArtifactPath is absent, write the standalone runtime summary under .hex-skills/runtime-artifacts/runs/{run_id}/evaluation-worker/{worker}--{identifier}.json and optionally echo the same summary in structured output.

Report written: .hex-skills/runtime-artifacts/runs/{run_id}/audit-report/ln-612--architecture.md
Score: X.X/10 | Issues: N (C:N H:N M:N L:N)

Critical Rules

MANDATORY READ: Load shared/references/audit_worker_core_contract.md.

  • Read progressively: Use section-first reading; full reads only when needed for safe judgment
  • Scope inference: If no SCOPE tag, use document filename to infer expected scope
  • Doc-kind aware: Judge by document purpose, not one generic rubric
  • No false positives: Better to miss an issue than report incorrectly
  • Location precision: Always include line number for findings
  • Actionable fixes: Every finding must have concrete fix suggestion
  • No fact-checking: Do NOT verify paths, versions, endpoints against code
  • Shared class registry: Document boundaries come from docs_quality_contract.md; do not invent alternate scope rules per file

Definition of Done

MANDATORY READ: Load shared/references/audit_worker_core_contract.md.

  • Header contract extracted or inferred
  • Content-scope alignment analyzed (OFF_TOPIC, MISSING_COVERAGE, SCOPE_CREEP, SSOT_VIOLATION)
  • Semantic judgment applied according to DOC_KIND
  • Score calculated using penalty algorithm
  • Report written to {output_dir}/ln-612--{doc-slug}.md (atomic single Write call)
  • Summary written per contract

Reference Files

  • Audit output schema: shared/references/audit_output_schema.md

Version: 2.0.0 Last Updated: 2026-03-01

平台分布

Codex

34.71%
按下载量换算420

Claude

28.74%
按下载量换算348

Cursor

19.43%
按下载量换算235

Gemini CLI

9.83%
按下载量换算119

安全审计

Gen Agent Trust Hub

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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