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Agent Skill · 研究检索

brownfield-onboarding(棕地入职)

brownfield-onboarding 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。

brownfield-onboarding 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,权限为需要联网;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 59,464。

总安装 388周安装 16GitHub Stars 1下载 127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:brownfield-onboarding(棕地入职)
来源仓库:https://github.com/cyberelf/agent_skills
仓库路径:skills/brownfield-onboarding
安装命令:
npx skills add https://github.com/cyberelf/agent_skills --skill brownfield-onboarding
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/cyberelf/agent_skills --skill brownfield-onboarding

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。

brownfield-onboarding 用于快速理解陌生或继承型项目的结构与设计决策。它生成架构文档、改进建议与 AI 代理宪法文件,加速新人上手与协作效率。使用时适合启动新项目或接手遗留系统,输出包含 UI/UX 指南的完整知识包。文档应由人类开发者校验准确性,避免 AI 推断导致误解关键业务逻辑。

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。

来源仓库内路径:skills/brownfield-onboarding

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/cyberelf/agent_skills --skill brownfield-onboa…;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

    它需要需要联网,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

brownfield-onboarding 怎么安装?

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

brownfield-onboarding 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。

brownfield-onboarding 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

brownfield-onboarding 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。

brownfield-onboarding 用的人多吗?

公开数据是累计安装 388 次,近一周安装 16 次,下载 127 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。

brownfield-onboarding 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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
brownfield-onboarding

棕地入职 · 本页

3881需要联网未明确未通过

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

Brownfield Project Onboarding

Overview

This skill provides a systematic approach to understand and document existing projects. It helps developers quickly get up to speed with unfamiliar codebases by generating comprehensive documentation about the project's structure, architecture, design decisions, identifying areas for improvement, and creating AI agent constitution files (AGENTS.md) that encode project-specific knowledge, coding principles, and UI/UX guidelines for effective AI-assisted development.

When to Use This Skill

Invoke this skill when:

  • Starting work on an unfamiliar or inherited codebase
  • Joining a new team or project
  • Conducting a technical audit of an existing system
  • User requests "help me understand this project"
  • Need to document an undocumented or poorly documented project
  • Preparing for a major refactoring or modernization effort
  • Setting up AI agent constitution files for better AI-assisted development
  • Establishing coding principles and standards for a team
  • Creating comprehensive context for AI agents working on the project

How This Skill Works

Upon invocation, this skill:

  1. Analyzes the project to determine its documentation state
  2. Selects the appropriate workflow based on project maturity
  3. Executes the workflow to generate comprehensive documentation
  4. Creates or enhances AGENTS.md files for AI agent context
  5. Provides actionable recommendations for improvements

Workflow Selection

This skill uses different workflows based on the project's current state:

Project State Detection

The AI agent automatically analyzes the project to determine its documentation maturity level.

Detection Process:

  1. Search for AGENTS.md files using file_search
  2. Search for constitution/guideline files (.cursorrules, CONTRIBUTING.md, etc.)
  3. Read and analyze README for depth and quality
  4. Apply classification rules with intelligent judgment

Classification States:

  • MATURE: AGENTS.md exists
  • ESTABLISHED: Constitution files + substantial README (>100 lines)
  • PARTIAL: Basic README (>50 lines) only
  • VANILLA: Minimal/no documentation (default)

Detection Logic:

  • Has AGENTS.md → MATURE
  • Has constitution files + README >100 lines with depth → ESTABLISHED
  • Has README >50 lines of meaningful content → PARTIAL
  • Otherwise → VANILLA (default)

The agent uses its intelligence to assess quality, not just quantity. A 60-line README with architecture details is better than a 150-line changelog.

Workflow Files

Based on the agent's assessment, one of these workflows is executed:

Project StateWorkflow FileTimeUse When
Vanillavanilla-project.md15-25 minNo/minimal docs, no constitutions
Partial Docspartial-documentation.md10-20 minHas README, no constitutions
Establishedestablished-project.md10-15 minGood docs, has constitutions, no AGENTS.md
Maturemature-project.md5-10 minAlready has AGENTS.md files

📖 For detailed workflow selection logic, see decision-guide.md


Core Workflow Phases

All workflows execute these five phases (adapted to project state):

Phase 1: Project Discovery

  • Scan codebase structure
  • Identify technologies and frameworks
  • Discover features and entry points
  • Output: .onboard/overview.md

Phase 2: Architecture Analysis

  • Document technical stack
  • Identify architectural patterns
  • Map data flow
  • Output: .onboard/architecture.md

Phase 3: Design Assessment

  • Evaluate code quality
  • Identify technical debt
  • Propose improvements
  • Output: .onboard/design_suggestions.md

Phase 4: Quality & Automation Review

  • Assess testing coverage
  • Evaluate CI/CD maturity
  • Recommend improvements
  • Output: .onboard/guardrail_suggestions.md

Phase 5: Agent Constitution Generation

  • Detect/read existing constitutions
  • Generate or enhance AGENTS.md files
  • Create project-specific guidelines
  • Outputs: AGENTS.md files + .onboard/agent_constitution.md

Execution Instructions

Step 1: Detect Project State

Analyze the project to determine its documentation maturity:

  1. Search for AGENTS.md: Use file_search with pattern **/AGENTS.md

- If found → State is MATURE

  1. Search for constitution files: Use file_search to look for:

- .cursorrules - CONTRIBUTING.md - .github/CONSTITUTION.md - Linter configs (.eslintrc, .prettierrc, etc.) - Style guides

  1. Analyze README: Use read_file to check README.md

- Count lines of meaningful content (exclude headers, badges, empty lines) - Assess depth: Does it explain architecture, setup, contribution guidelines?

  1. Classify based on findings:

- Has AGENTS.md → MATURE - Has constitution files + substantial README (>100 lines) → ESTABLISHED - Has basic README (>50 lines) but no constitution → PARTIAL - Minimal/no README (<50 lines) → VANILLA (default)

Step 2: Load Appropriate Workflow

Based on your assessment, read and execute the corresponding workflow:

Step 3: Execute Workflow

Follow the instructions in the selected workflow file:

  • Each workflow provides detailed, phase-by-phase instructions
  • Each workflow adapts phases to the project's current state
  • Each workflow includes specific tool usage recommendations

Step 4: Validate Outputs

Ensure all expected files are generated:

  • .onboard/overview.md
  • .onboard/architecture.md
  • .onboard/design_suggestions.md
  • .onboard/guardrail_suggestions.md
  • .onboard/agent_constitution.md
  • ./AGENTS.md (created or enhanced)
  • Subdirectory AGENTS.md files (if applicable)

Step 5: Provide Summary

Give user a comprehensive completion summary based on workflow type.


AGENTS.md Templates

This skill includes template files for generating AGENTS.md:

Available Templates

  1. root-agents-template.md

- Project-wide context and coding principles - Placed at project root

  1. frontend-agents-template.md

- Frontend-specific guidelines - UI/UX design system and accessibility - Placed in frontend directory

  1. backend-agents-template.md

- Backend-specific guidelines - API design and security principles - Placed in backend directory

Template Adaptation

Templates are adapted based on:

  • Actual project structure and patterns
  • Discovered design tokens and conventions
  • Existing constitution file content
  • Tech stack and framework conventions

Key Principles

1. Non-Destructive Enhancement

  • Never overwrite existing documentation
  • Enhance and complement, don't replace
  • Preserve existing constitution files
  • Mark all additions clearly

2. Context-Aware Generation

  • Generate content based on actual code analysis
  • Use project-specific examples
  • Adapt to detected patterns
  • Match existing documentation style

3. Workflow Adaptation

  • Different approaches for different project maturities
  • Respect existing work and conventions
  • Focus effort where value is highest
  • Minimize disruption to established projects

4. AI Agent Optimization

  • Create machine-readable guidelines
  • Include validation checklists
  • Provide quick reference formats
  • Synthesize across multiple docs

Common Tools Used

Across all workflows, these tools are commonly used:

Discovery Tools

  • list_dir - Explore directory structure
  • file_search - Find specific files by pattern (e.g., **/AGENTS.md, **/.cursorrules)
  • read_file - Read documentation and config files (README, CONTRIBUTING, etc.)

Analysis Tools

  • semantic_search - Find features and concepts
  • grep_search - Pattern-based code search
  • list_code_usages - Understand code relationships

Validation Tools

  • get_errors - Identify existing issues
  • Code analysis for patterns and anti-patterns

Output Directory Structure

After execution, the workspace contains:

.onboard/
├── overview.md              # Project structure and features
├── architecture.md          # Technical stack and architecture
├── design_suggestions.md    # Improvement recommendations
├── guardrail_suggestions.md # Testing and CI/CD recommendations
└── agent_constitution.md    # Constitution generation summary

AGENTS.md                    # Root project constitution
[frontend]/AGENTS.md         # Frontend guidelines (if applicable)
[backend]/AGENTS.md          # Backend guidelines (if applicable)

Notes & Best Practices

  • Comprehensive Analysis: Take time to thoroughly explore before documenting
  • Be Specific: Include file paths and concrete examples
  • Prioritize: Rank suggestions by impact and effort
  • Actionable: Provide implementable recommendations
  • Context-Aware: Tailor to project size, domain, and maturity
  • Positive Framing: Start with strengths before improvements
  • Realistic Estimates: Provide effort estimates for planning
  • Agent-Friendly: Enable AI agents to validate their work
  • Respect Existing Constitutions: Enhance rather than replace
  • Non-Destructive: Always preserve existing content when merging
  • Context-Rich Constitutions: Make AGENTS.md comprehensive with project-specific details

Common Pitfalls to Avoid

  • ❌ Generating superficial documentation without deep analysis
  • ❌ Making technology recommendations without understanding constraints
  • ❌ Suggesting major rewrites instead of incremental improvements
  • ❌ Ignoring existing documentation or architectural decisions
  • ❌ Providing generic advice that doesn't apply to the specific project
  • ❌ Overwhelming with too many suggestions without prioritization
  • ❌ Missing critical security or performance issues
  • ❌ Overwriting existing constitution files without preserving original content
  • ❌ Creating generic AGENTS.md templates without project-specific context
  • ❌ Skipping UI/UX principles analysis for frontend projects

Extension Points

This skill can be extended to include:

  • Security Audit: Dedicated security vulnerability assessment
  • Performance Profiling: Performance bottleneck identification
  • Accessibility Review: WCAG compliance checking for web apps
  • API Documentation: Automated API documentation generation
  • Database Analysis: Schema design review and optimization suggestions
  • UI/UX Deep Dive: Integration with ui-ux-pro-max skill for comprehensive UI/UX principles
  • Dependency Audit: Automated dependency security and license checking
  • Constitution Compliance: Automated checking of code against AGENTS.md guidelines

Related Skills

  • ui-ux-pro-max: Can be invoked for comprehensive UI/UX analysis to enhance frontend AGENTS.md files
  • openspec-constitution-guard: Can validate code changes against generated AGENTS.md constitutions
  • issue-fixer: Uses project context from AGENTS.md files to fix issues more effectively
  • retrospect: References AGENTS.md for project-specific context during retrospective analysis

Reference Documentation

Workflow References

Template References


Quick Start

To use this skill:

  1. User invokes: "Help me understand this project" or "Run brownfield onboarding"
  2. Detect project state: Analyze project to determine maturity level (MATURE/ESTABLISHED/PARTIAL/VANILLA)
  3. Load workflow: Read the appropriate workflow file from references/
  4. Execute phases: Follow workflow instructions for all 5 phases
  5. Generate outputs: Create all documentation and AGENTS.md files
  6. Provide summary: Give user comprehensive results and next steps

The workflow files contain all detailed instructions - this main SKILL.md serves as the orchestration guide.

平台分布

Codex

34.03%
按下载量换算43

Claude

29.88%
按下载量换算38

Cursor

18.77%
按下载量换算24

Gemini CLI

8.75%
按下载量换算11

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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