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Agent Skill · 研究检索

authoring-technical-docs(撰写技术文档)

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。

authoring-technical-docs 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,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 55,679。

总安装 470周安装 19GitHub Stars 5下载 147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:authoring-technical-docs(撰写技术文档)
来源仓库:https://github.com/wizeline/sdlc-agents
仓库路径:skills/authoring-technical-docs
安装命令:
npx skills add https://github.com/wizeline/sdlc-agents --skill authoring-technical-docs
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/wizeline/sdlc-agents --skill authoring-technical-docs

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。

定义技术文档工程流程,涵盖研究、起草、自评与格式化四大阶段。提供风格规则、质量检查与多轮修订机制,支撑高质量交付。是所有技术写作类技能(API、架构、发布)的基础依赖。安装需通过 npx skills add 添加 sdlc-agents 仓库中的 authoring-technical-docs 技能。

执行任何文档动作前必须首先加载此技能以继承通用框架。

来源仓库内路径:skills/authoring-technical-docs

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/wizeline/sdlc-agents --skill authoring-technic…;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

authoring-technical-docs 怎么安装?

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

authoring-technical-docs 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。

authoring-technical-docs 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。

authoring-technical-docs 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。

authoring-technical-docs 用的人多吗?

公开数据是累计安装 470 次,近一周安装 19 次,下载 147 次,GitHub 5 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。

authoring-technical-docs 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

  • 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

  • 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
authoring-technical-docs

撰写技术文档 · 本页

4705调用外部服务未明确通过

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

Authoring Technical Docs — Core Documentation Engineering Action

Overview

This action defines the process, quality standards, and style rules for producing professional technical documentation. It follows a multi-pass workflow: research the inputs, draft the document, self-review for quality, and format for delivery.

Always load this action first. Domain actions (authoring-api-docs, authoring-architecture-docs, authoring-release-docs, authoring-user-docs) build on this foundation.


Workflow

Execute these phases in order. Do not skip phases.

Request → RESEARCH → DRAFT → REVIEW → REVISE (max 2 cycles) → FORMAT → Deliver

Phase 1: Research

Before writing a single word, consume every input artifact and build a structured understanding. Documentation is 80% research, 20% writing.

What to extract

From source code: function/method signatures, class hierarchies, module structure, docstrings, inline comments, error types, dependencies.

From OpenAPI / Swagger specs: all endpoints with methods, paths, parameters, request/response schemas, auth requirements, rate limits.

From PRDs / product specs: user stories, acceptance criteria, target personas, feature scope and non-goals, business context. *use MCP tool to connect with Confluence*

From existing documentation: current structure and coverage, last-updated dates, terminology used, gaps relative to codebase.

From Jira / ticket exports: feature descriptions, bug descriptions, resolution status, linked PRs, labels. *use MCP tool to connect with JIRA*

Audience identification

If not stated, infer from context:

  • API spec + no UI docs → developer
  • UI mockups + user stories → end-user
  • Infrastructure code + deployment configs → operator/admin
  • Architecture diagrams + design decisions → internal engineering

State the inference so the user can correct it.

Gap detection (highest-value research activity)

Check for:

  1. Spec-code mismatches — spec says one thing, code does another
  2. Missing information — feature in PRD but no corresponding code
  3. Stale references — docs reference things no longer in the code
  4. Undocumented behavior — code handles edge cases no spec mentions
  5. Contradictions — two sources disagree on the same fact

Classify each gap:

  • Blocker — can't write accurate docs without resolution. Surface to user before drafting.
  • Warning — can write around it, should verify
  • Info — nice to know

Documentation type (Diátaxis framework)

  • Tutorial — audience is new, feature is complex, hands-on learning needed
  • How-To Guide — audience knows basics, needs to accomplish a specific task
  • Explanation — the "why" needs communicating, decisions need context
  • Reference — precise technical details need cataloguing

Share a brief research summary before proceeding to drafting.


Phase 2: Draft

Write the document following the style rules below and the domain action's templates.

Non-negotiable style rules

RuleDoDon't
Voice"The API returns a JSON object""A JSON object is returned by the API"
Person"You can configure...""The user can configure..."
Tense"This endpoint accepts...""This endpoint will accept..."
Instructions"Click Save.""You should click Save."
Headings"Set up your environment" (sentence case)"Setting Up Your Environment"
ListsOxford comma: "logs, metrics, and traces""logs, metrics and traces"
JargonDefine on first use: "the payload (the data sent in the request body)"Undefined jargon
SentencesOne idea per sentence. Max ~25 words.Long compound sentences

YAML frontmatter (most important fields)

---
title: "[Document title]"
description: "[One-line description]"
audience: [developer | end-user | admin | operator]
doc-type: [tutorial | how-to | reference | explanation]
version: [X.X]
last-updated: [YYYY-MM-DD]
---

Handling gaps

  • Blocker gaps: <!-- [GAP: description — needs human verification] -->
  • Warning gaps: Write best available version, add <!-- [UNVERIFIED: description] -->
  • Never invent facts. A visible gap is better than a hidden error.

Code examples

  • Every API endpoint or function gets at least one working example
  • Complete and runnable — no ... or // rest of code
  • Placeholder values clearly marked: YOUR_API_KEY, <project-id>
  • Pair request examples with expected responses

Phase 3: Review (self-critique)

After drafting, switch to critic mode. Apply the First-Party Consumption Principle: read the draft as the target audience encountering it for the first time. Ask: "Could I accomplish the goal using ONLY this document?"

Six quality dimensions

  1. Accuracy — every factual claim traceable to a source input
  2. Completeness — no missing parameters, steps, or sections; prerequisites listed; error handling present
  3. Usability — each procedure step is unambiguous; code examples are runnable
  4. Consistency — same term used throughout; heading style uniform; code examples use same conventions
  5. Readability — sentences ≤25 words; no passive voice; no undefined jargon
  6. Structure — heading hierarchy sequential; info flows general → specific; code blocks have language tags

Issue severity

  • Blocker: factual error, missing prerequisite, broken code example, wrong audience, missing critical section
  • Major: passive voice, missing error handling, undefined jargon, ambiguous pronoun, inconsistent terminology
  • Minor: missing Oxford comma, title case heading, future tense, third person

If blockers or major issues found → revise. Maximum 2 revision cycles.


Phase 4: Format and deliver

  1. Fix heading hierarchy silently
  2. Ensure YAML frontmatter is complete
  3. Add language tags to untagged code blocks
  4. Generate table of contents if 4+ H2 sections
  5. Save to docs/ relative to project root with a descriptive filename

Unresolved issues

If any issues remain after revision cycles, append as editor's notes:

---

## Editor's notes

- [Issue description and suggested fix]

Guiding principles

  1. Documentation is 80% research, 20% writing. Never start writing before understanding the full picture.
  2. Source of Truth Principle. Every factual claim must trace to an input artifact.
  3. First-Party Consumption Principle. Read your own docs as if you're a first-time user.
  4. Flag, don't guess. Unclear → mark as gap, don't infer.
  5. Show, don't tell. Code examples and concrete scenarios beat abstractions.
  6. Progressive disclosure. Common path first, edge cases in variations.
  7. Every document ends somewhere. Always provide next steps.

平台分布

Codex

35.74%
按下载量换算53

Claude

28.71%
按下载量换算42

Cursor

19.02%
按下载量换算28

Gemini CLI

8.99%
按下载量换算13

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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。目前只有一个公开来源,建议同时核对源仓库。

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