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Agent Skill · 研究检索

technical-writer(技术作家)

technical-writer 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。

technical-writer 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,权限为接触敏感数据;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 72,323。

总安装 188周安装 8GitHub Stars 1下载 66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:technical-writer(技术作家)
来源仓库:https://github.com/hungv47/prod-skills
仓库路径:skills/technical-writer
安装命令:
npx skills add https://github.com/hungv47/prod-skills --skill technical-writer
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/hungv47/prod-skills --skill technical-writer

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。

用于查找、检索和筛选相关信息,支持基于关键词定位内容。适用于需要快速筛选候选结果的场景。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。可通过 GitHub 仓库路径和技能名称进行安装。使用前需确认权限范围及是否触发网络或文件操作。

technical-writer 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/technical-writer

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/hungv47/prod-skills --skill technical-writer;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

    它需要接触敏感数据,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

technical-writer 怎么安装?

在终端执行 npx skills add https://github.com/hungv47/prod-skills --skill technical-writer。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

technical-writer 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。

technical-writer 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

technical-writer 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。

technical-writer 用的人多吗?

公开数据是累计安装 188 次,近一周安装 8 次,下载 66 次,GitHub 1 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。

technical-writer 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
technical-writer

技术作家 · 本页

1881接触敏感数据未明确通过

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

Technical Writer — Orchestrator

*Productivity — Multi-agent orchestration. Scans a codebase and produces clear, structured documentation that new users can follow without reading source code.*

Core Question: "Could a new team member understand this without asking anyone?"

Inputs Required

  • A codebase or project to document
  • (Optional) Target audience — developer, end-user, operator, or mixed
  • (Optional) Documentation type — README, User Guide, API Reference, or Configuration Guide

Output

  • Documentation artifact saved to project root or specified location (e.g., docs/, README.md)

Chain Position

Previous: none | Next: none (standalone)

Pairs well with: system-architecture (for architecture docs), task-breakdown (for contributor guides)

Re-run triggers: After PRs that modify environment variables, API routes, or configuration. After major version releases. When new features ship without documentation updates.


Multi-Agent Architecture

Agent Roster

AgentFileFocus
scanner-agentagents/scanner-agent.mdMaps project structure, file importance ranking, existing docs inventory
concept-extractor-agentagents/concept-extractor-agent.mdReads key files, extracts features, setup requirements, error patterns
audience-profiler-agentagents/audience-profiler-agent.mdIdentifies audience, calibrates vocabulary and depth
writer-agentagents/writer-agent.mdWrites the documentation from extracted concepts for the profiled audience
staleness-checker-agentagents/staleness-checker-agent.mdCompares documentation against current codebase for accuracy
critic-agentagents/critic-agent.mdQuality gate review, audience calibration check, staleness integration

Execution Layers

Layer 1 (parallel):
  scanner-agent ──────────────┐
  concept-extractor-agent ────┤── run simultaneously
  audience-profiler-agent ────┘

Layer 2 (sequential):
  writer-agent ────────────────── writes documentation from all Layer 1 outputs
    → staleness-checker-agent ─── verifies documentation matches codebase
      → critic-agent ──────────── final quality review

Dispatch Protocol

  1. Layer 1 dispatch — send brief to all three Layer 1 agents in parallel:

- scanner-agent maps the project and ranks files by importance - concept-extractor-agent reads ranked files and extracts documentation content - audience-profiler-agent determines who reads the docs and how to write for them

  1. Writer dispatch — send all Layer 1 outputs to writer-agent. It produces the documentation following references/doc-template.md, calibrated for the audience.
  2. Staleness check — send writer output + codebase facts to staleness-checker-agent. It verifies every claim in the docs matches the current codebase.
  3. Critic review — send documentation + staleness results to critic-agent.
  4. Revision loop — if critic returns FAIL, re-dispatch affected agents. Maximum 2 rounds.
  5. Save — write documentation to project root or specified location.

Routing Rules

ConditionRoute
User specifies audienceaudience-profiler-agent uses it directly (no inference needed)
User says "document this" (no type)audience-profiler defaults to User Guide (developers) or README (library)
User says "audit docs"Skip writer-agent; run scanner → staleness-checker → critic directly
Monorepo detectedscanner-agent identifies package boundaries; writer produces per-package docs
Critic PASSSave and deliver
Critic FAILRe-dispatch cited agents with feedback

Critical Gates

Before delivering, the critic-agent verifies ALL of these pass:

  • Every user-facing feature has a documentation section
  • Setup steps are numbered with expected outcomes after each step
  • A new user could follow Getting Started independently without reading source code
  • Code examples compile/run — no pseudocode unless explicitly labeled
  • Configuration options list defaults and valid values
  • Troubleshooting covers errors visible in the codebase's error handling

If any gate fails: the critic identifies which agent must fix it and the orchestrator re-dispatches.


Single-Agent Fallback

When context window is constrained or the project is small (fewer than 20 files):

  1. Skip multi-agent dispatch
  2. Scan project structure and identify key files using the 7-rank importance system
  3. Read 5-10 highest-ranked files
  4. Determine audience (developer, end-user, operator)
  5. Write documentation following references/doc-template.md
  6. Cross-check env vars, setup steps, and API endpoints against code
  7. Run Critical Gates as self-review
  8. Save to project root or specified location

Documentation Types

TypeAudienceFocusLength
READMEDevelopers discovering the projectWhat it does, quick start, contribution1-3 pages
User GuideEnd-users operating the productWorkflows, features, troubleshooting5-20 pages
API ReferenceDevelopers integratingEndpoints, parameters, responses, errorsVaries
Configuration GuideOperators deployingEnvironment vars, settings, infrastructure2-5 pages
Getting Started TutorialNew users of any typeSingle workflow, start to finish1-2 pages

Default to User Guide if the user says "document this" without specifying type.


File Importance Ranking (7 Ranks)

The scanner-agent ranks files by documentation value:

RankFile TypeWhat It RevealsPriority
1Entry points (main.*, index.*, app.*)App initialization, core structureRead first
2Route/endpoint definitionsFeature surface areaRead second
3Config/env filesSetup requirements, feature flagsRead third
4Models/Types/SchemasCore data entities, relationshipsRead for depth
5Components/ViewsUI structure, user interactionsRead for UX docs
6Middleware/InterceptorsAuth, logging, error handlingRead for ops docs
7Migration filesData model evolution, schema requirementsSkim for setup

3 Audience Types

AudienceVocabularyCode ExamplesAssumed Knowledge
End-userPlain language, no jargonOnly CLI commands they runCan install software, use a browser
DeveloperTechnical terms, API vocabularyRequest/response samples, code snippetsCan read code, use package managers
OperatorInfrastructure terminologyConfig files, deployment commandsUnderstands networking, servers, CI/CD

Documentation Audit Mode

Trigger when asked to "audit docs", "check documentation", or "are docs up to date."

In audit mode, the orchestrator skips the writer-agent and runs:

  1. scanner-agent — inventory all documentation files
  2. staleness-checker-agent — compare each doc against current codebase
  3. critic-agent — report findings with priority (security-relevant > setup > architecture > everything else)

Prioritize: auth docs and env var docs being stale is a security risk.


Anti-Patterns

Anti-PatternProblemINSTEAD
Restating code as prose"handleSubmit handles form submission" adds nothingwriter-agent describes user experience, not internal code
Missing prerequisitesUser stuck at step 3 because step 0 was assumedconcept-extractor lists every dependency and version
Wall of textUsers scan, not read — long paragraphs get skippedwriter-agent uses tables, numbered lists, headers
Outdated screenshotsScreenshots rot faster than textwriter-agent prefers text descriptions of UI elements
Documenting internalsUsers don't care about ORM layerwriter-agent documents behavior and interfaces
"See code for details"Defeats purpose of documentationconcept-extractor extracts the relevant detail
Stale docs shipped as currentActively mislead usersstaleness-checker verifies every claim against codebase

Worked Example

User: "Document this project" (a Node.js REST API for task management)

Layer 1 (parallel):

  • scanner-agent → maps project: src/index.ts, src/routes/, src/models/, prisma/schema.prisma, package.json,.env.example. Existing README is stale (references Node 16, project uses Node 18).
  • concept-extractor-agent → reads ranked files: Express app with JWT auth, task CRUD with status workflow (todo→in-progress→done), team assignment, email notifications. Errors: 401 expired token, 403 cross-team access, 422 invalid status transition.
  • audience-profiler-agent → Developer audience (API consumers). Recommended type: README + API Reference.

Layer 2 (sequential):

  • writer-agent → writes README with Getting Started (5 numbered steps), API Reference, Configuration table, Troubleshooting section
  • staleness-checker-agent → flags: Node version in setup (docs say 16, code needs 18), missing SMTP_PORT env var (in code but not documented)
  • critic-agent → FAIL: 2 staleness issues must be fixed

Revision: writer-agent updates Node version and adds SMTP_PORT. Critic → PASS.

Artifact saved to README.md.


Before Starting

Step 0: Product Context

Check for existing context files: README.md, CLAUDE.md, .agents/product-context.md, package.json#description. Read all available context before scanning code.

Optional Artifacts

ArtifactSourceBenefit
product-context.mdicp-research (from hungv47/marketing-skills)Product positioning and audience already defined
system-architecture.mdsystem-architectureArchitecture decisions pre-mapped
.agents/design/brand-system.mdbrand-system (from hungv47/marketing-skills)Brand voice and terminology guidelines

Artifact Template

On re-run: rename existing artifact to [name].v[N].md and create new with incremented version.

---
skill: technical-writer
version: 1
date: {{today}}
status: draft
audience: [end-user | developer | operator | mixed]
doc-type: [readme | user-guide | api-reference | config-guide | tutorial]
---

References

平台分布

Codex

32.95%
按下载量换算22

Claude

29.17%
按下载量换算19

Cursor

19.21%
按下载量换算13

Gemini CLI

9.62%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。目前只有一个公开来源,建议同时核对源仓库。

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