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setup-docs设置文档

Agent Skill

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。

总安装

256

周安装

11

GitHub Stars

5

下载量

90
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:setup-docs(设置文档)
来源仓库:https://github.com/generaljerel/chalk-skills
仓库路径:skills/setup-docs
安装命令:
npx skills add https://github.com/generaljerel/chalk-skills --skill setup-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/generaljerel/chalk-skills --skill setup-docs

简介

用于辅助文档、README 和 Markdown 内容整理。

  • 适合提炼结构、补齐章节、统一术语或检查链接。
  • 通过 npx skills add 命令从 generaljerel/chalk-skills 仓库安装。
  • 使用时应保留项目已有事实,避免将未确认信息写成确定结论。
  • setup-docs 属于前端设计类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

One-shot bootstrap that deeply analyzes the codebase and populates all .chalk/docs/ PROFILE stubs with real, project-specific content. Also enriches chalk.json with any fields that setup-chalk couldn't auto-detect.

When to Use

  • After running /setup-chalk or npx create-chalk to generate stub docs
  • When PROFILE docs contain <!-- STUB --> markers or placeholder content
  • When chalk.json has missing fields (routes, sourceLayout, etc.)
  • To refresh docs after significant codebase changes

Workflow

Step 1: Read existing state

  1. Read chalk.json — Check which fields are populated vs missing. Note any that need enrichment (especially routes, sourceLayout, dev).
  2. Read each PROFILE doc — Skip any that are already populated (no <!-- STUB --> comment and more than 20 lines of real content). Note which verticals need work.
  3. Read the codebasepackage.json, README.md, src/ directory structure, config files, and any existing docs.

Step 2: Enrich chalk.json

Fill any missing fields by deep analysis:

  • routes — If empty, scan the codebase:

- File-based routing: glob for app/**/page.{tsx,jsx} or pages/**/*.{tsx,vue} - React Router: grep for <Route path= or createBrowserRouter - Vue/Angular: grep router configs - Express/API: grep for app.get(, router. - For each route found, identify the source file/directory

  • sourceLayout — If empty, scan for standard directories (src/, app/, lib/, components/, pages/, tests/)
  • dev — If missing port/url, check vite.config, next.config, or framework defaults
  • test — If missing, check for jest.config, vitest.config, pytest.ini, or test scripts in package.json

Write the updated chalk.json with any new fields.

Step 3: Populate Product Profile (.chalk/docs/product/PROFILE.md)

Deep analysis to populate:

  • Summary: product name, one-liner, primary users, core JTBD, value prop
  • Problem: what pain this solves (infer from README, package.json description)
  • Target Users: table (Persona, Job, How This Helps)
  • Core Jobs To Be Done: numbered list (infer from features, routes, UI patterns)
  • Current Status: table of features (Feature, Status, Notes)
  • What It Is / What It Is Not: clarify scope

Step 4: Populate Engineering Profile (.chalk/docs/engineering/PROFILE.md)

Deep analysis to populate:

  • Architecture: process model diagram, execution contexts table, boot sequence
  • Directory Structure: annotated tree with purpose per directory
  • Data Flow: state management, API/IPC boundaries, storage layer
  • Tech Stack: full dependency tables (runtime + dev/build), grouped by category
  • Key Patterns: design patterns, error handling, testing approach

This is a single comprehensive doc — do NOT create separate architecture or techstack files.

Step 5: Populate Coding Style (.chalk/docs/engineering/coding-style.md)

Analyze 5+ representative files across different layers to document:

  • File/folder naming conventions with real examples
  • Component/module structure with a full code example from the codebase
  • Naming conventions (variables, functions, types, files)
  • Import ordering with a real example
  • Export patterns
  • TypeScript/language-specific patterns
  • Styling approach
  • Error handling patterns

Step 6: Populate AI Profile (.chalk/docs/ai/PROFILE.md)

Create the agent orientation doc:

  • Project Identity: 1 paragraph summary
  • Where Things Live: table (What, Where, Notes) — map every major concern to its file/directory
  • Conventions to Follow: top 5-10 rules for writing code in this project
  • Gotchas: numbered list of things that will surprise an agent
  • How to Add a Feature: step-by-step guide based on codebase patterns

Step 7: Populate Design Profile (.chalk/docs/design/PROFILE.md)

Extract visual language:

  • Color Palette: scan CSS files, Tailwind config, and components for hex codes and Tailwind classes. Organize into Primary, Neutral, and Semantic tables.
  • Typography: font families, size scale, weight scale from CSS/config
  • Spacing: recurring padding/margin values
  • Borders & Shadows: border widths, radius, shadow definitions
  • Icons: icon library and common icons used
  • Component Patterns: common UI patterns (buttons, cards, panels)

Step 8: Update AGENTS.md

If AGENTS.md exists, enrich with project-specific pointers to the populated docs and critical conventions. If it doesn't exist, create a minimal one pointing to .chalk/docs/.

Step 9: Confirm

List what was populated, what was skipped, and any remaining gaps. Suggest next steps (e.g., "Design profile has placeholder content — run /update-doc design/PROFILE.md to refine").

Rules

  • Write substantive content, not stubs — Every section should have real information from the codebase analysis.
  • Remove <!-- STUB --> markers — When populating a doc, remove the stub comment.
  • Preserve existing content — If a doc already has real content in some sections, enhance rather than overwrite.
  • Use the vertical's tone — Product docs are business-facing. Engineering docs are technical. AI docs are agent-facing reference.
  • Include the "Last updated" line — Format: Last updated: YYYY-MM-DD (populated from codebase analysis).
  • chalk.json is authoritative — If chalk.json disagrees with a PROFILE doc, chalk.json wins. Update the doc to match.
  • Real examples over abstractions — Always use actual code, file paths, and values from the codebase.

Differences from related skills

  • /setup-chalk creates the .chalk/ scaffold with stubs — run it first
  • /setup-docs populates those stubs with real content — run it second
  • /create-doc creates a single new doc for a specific topic on demand
  • /update-doc updates an existing doc with new information
  • /validate-chalk checks if chalk.json and docs are complete and correct

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

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

38.25%
按下载量换算34

Claude

30.17%
按下载量换算27

Cursor

17.01%
按下载量换算15

Gemini CLI

9.38%
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

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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

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