Agent skill

Harness Step1 Create Agents Md

by simbajigege in simbajigege/book2skills

Harness Engineering 第一阶段:扫描现有项目,生成 AGENTS.md(目录文件)和完整的 docs/ 知识库结构。

Apache-2.0Auto-check passedAgent Workflows

Install Harness Step1 Create Agents Md

skills CLI
$ npx skills add simbajigege/book2skills --skill harness-step1-create-agents-md -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install simbajigege/book2skills harness-step1-create-agents-md --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/simbajigege/book2skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/harness-step1-create-agent-md .claude/skills/harness-step1-create-agents-md && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
harness-step1-create-agents-md
GitHub stars
183
Token cost
~1.1k tokens
SKILL.md length
141 words
Files
7
Skills in repo
37
Repo updated
First seen
Licence
Apache-2.0

At a glance

Harness Engineering 第一阶段:扫描现有项目,生成 AGENTS.md(目录文件)和完整的 docs/ 知识库结构。

  • Works in 4 steps: :扫描项目 → :生成 docs/ 目录结构 → :写 AGENTS.md → …
  • Tasks that involve Building AI agents
  • SKILL.md covers 目标, 执行步骤, 质量检验 and 完成后告知用户
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Harness Step1 Create Agents Md is an agent skill from simbajigege/book2skills. Harness Engineering 第一阶段:扫描现有项目,生成 AGENTS.md(目录文件)和完整的 docs/ 知识库结构。 当用户想要"为项目添加 agent 支持"、"让 AI 更好地理解我的项目"、"开始 harness engineering"、 "创建 AGENTS.md"、"搭建 agent 文档结构"、"让 Claude Code 更好地工作"时,立即使用此 skill。 也适用于用户说"帮我把项目文档整理好给 agent 用"、"我想开始用 AI agent 开发"、 "梳理这个项目能解决什么业务问题"或要求建立 business-solution.md 等场景。

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files (for example `README.md`, `en/harness-step1-create-agent-md.md` and `examples/en.yaml`).

It sits in Agent Workflows, covering Building AI agents and Agent instruction files. The repository describes itself as: Create best skills based on best books. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Building AI agents
  • Tasks that involve Agent instruction files

Example prompts

  • “为项目添加 agent 支持”
  • “让 AI 更好地理解我的项目”
  • “开始 harness engineering”
  • “/harness-step1-create-agents-md”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. :扫描项目
  2. :生成 docs/ 目录结构
  3. :写 AGENTS.md
  4. :写各个 docs/ 文件

What it can do on your machine

Read from SKILL.md and the folder at commit e5ba66c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash and markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Harness Step1 Create Agents Md loads about 1.1k tokens when it runs. Until then it costs about 83 tokens; SKILL.md has 141 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~83
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from simbajigege/book2skills at commit e5ba66c, republished under its Apache-2.0 licence (© simbajigege). 141 words, ~1,146 tokens.

Download SKILL.mdSave it as .claude/skills/harness-step1-create-agents-md/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
harness-step1-create-agents-md
description
Harness Engineering 第一阶段:扫描现有项目,生成 AGENTS.md(目录文件)和完整的 docs/ 知识库结构。 当用户想要"为项目添加 agent 支持"、"让 AI 更好地理解我的项目"、"开始 harness engineering"、 "创建 AGENTS.md"、"搭建 agent 文档结构"、"让 Claude Code 更好地工作"时,立即使用此 skill。 也适用于用户说"帮我把项目文档整理好给 agent 用"、"我想开始用 AI agent 开发"、 "梳理这个项目能解决什么业务问题"或要求建立 business-solution.md 等场景。

Harness Step 1: 创建 AGENTS.md 与 docs/ 知识库

目标

为项目建立 agent 可读的知识库地基:

  • 一份简短的 AGENTS.md(~100 行,作为"目录"而非百科全书)
  • 一套 docs/ 目录结构,存放真正的知识

核心原则:agent 看不到的东西就不存在。项目的业务定位、目标用户、解决的问题、架构决策、命名约定和技术选型,必须以文件形式存在于仓库中。


执行步骤

Step 1:扫描项目

按顺序收集项目信息,已知信息跳过,不要重复提问:

bash
# 1. 项目根目录结构(2层)
find . -maxdepth 2 -not -path '*/node_modules/*' -not -path '*/.git/*' \
  -not -path '*/__pycache__/*' -not -path '*/dist/*' -not -path '*/.next/*' | sort

# 2. 识别技术栈
cat package.json 2>/dev/null || cat pyproject.toml 2>/dev/null || \
  cat go.mod 2>/dev/null || cat Cargo.toml 2>/dev/null || echo "未找到包管理文件"

# 3. 查看是否已有文档
ls -la *.md 2>/dev/null; ls -la docs/ 2>/dev/null

# 4. 查看 README(如有)
head -80 README.md 2>/dev/null || head -80 readme.md 2>/dev/null

从扫描结果中提取:

  • 项目名称和用途(从 README 或 package.json)
  • 业务定位和用户价值(服务谁、解决什么问题、提供哪些可见能力)
  • 典型业务场景(从 README 功能、示例、截图说明和已有产品文档提取)
  • 技术栈(语言、框架、主要依赖)
  • 目录结构(主要模块划分)
  • 已有文档(避免重复,复用现有内容)

业务内容必须区分“仓库明确声明的现有能力”和“根据功能推断的潜在场景”。仅有营销描述、没有代码或产品文档证据的内容标注「待 Step 2 验证」。

Step 2:生成 docs/ 目录结构

创建以下文件(内容根据扫描结果填写,不要留空占位符):

必须创建的文件:

AGENTS.md                    ← 目录文件,~100行
docs/
├── business-solution.md     ← 业务定位、用户问题、解决方案和能力边界
├── ARCHITECTURE.md          ← 模块划分、依赖关系
├── CONVENTIONS.md           ← 命名规则、代码风格
├── TECH_DECISIONS.md        ← 技术选型理由
├── QUALITY.md               ← 验收标准、完成定义
└── exec-plans/
    ├── active/              ← 当前进行中的计划(空目录,放 .gitkeep)
    ├── completed/           ← 已完成的计划(空目录,放 .gitkeep)
    ├── backlog.md           ← 待开发功能列表(已知需求,尚未排期)
    └── tech-debt-tracker.md ← 已知技术债务

可选创建(根据项目实际情况判断):

docs/
├── design-docs/             ← 有复杂设计决策时创建
├── product-specs/           ← 有产品规格时创建
└── references/              ← 有外部文档需要本地化时创建
Step 3:写 AGENTS.md

严格遵守以下格式,控制在 100 行以内:

markdown
# [项目名称] — Agent 工作指南

## 这是什么项目
[1-3句话:项目用途、核心功能、服务对象]

## 快速定向
- **我在哪个目录?** 运行 `pwd` 确认工作目录
- **技术栈**:[语言] + [框架] + [主要工具]
- **入口文件**:[主要入口,如 src/main.ts、app/main.py]
- **启动命令**:[如何启动开发服务器]
- **测试命令**:[如何跑测试]

## 知识库地图
在做任何修改前,先阅读相关文档:

| 我想了解... | 去读这个文件 |
|------------|-------------|
| 业务定位、目标用户、解决什么问题 | `docs/business-solution.md` |
| 整体架构、模块划分 | `docs/ARCHITECTURE.md` |
| 命名规则、代码风格 | `docs/CONVENTIONS.md` |
| 技术选型原因 | `docs/TECH_DECISIONS.md` |
| 什么叫"完成" | `docs/QUALITY.md` |
| 当前进行中的计划 | `docs/exec-plans/active/` |
| 待开发功能列表 | `docs/exec-plans/backlog.md` |
| 已知技术债务 | `docs/exec-plans/tech-debt-tracker.md` |

## 工作规范
1. **改之前先读**:修改任何模块前,先读对应的架构文档
2. **完成即提交**:每个功能完成后立即 git commit,写清楚做了什么
3. **更新文档**:如果你的修改影响了架构或约定,同步更新 docs/
4. **不要猜**:看不懂的地方先读文档,文档没有再问

## 禁止事项
[根据项目实际情况填写,例如:]
- 不要直接修改 `generated/` 目录下的文件(自动生成)
- 不要跳过测试直接合并
- 不要在 service 层引用 UI 组件(见 docs/ARCHITECTURE.md)
Step 4:写各个 docs/ 文件

每个文件的内容要求:

docs/business-solution.md

  • 一句话业务定位,以及项目不是什么
  • 目标用户/角色和各自的核心任务
  • 当前业务痛点与项目能力的对应关系
  • 3-8 个有证据支持的典型业务场景
  • 一条核心端到端业务流程(从用户输入到获得业务结果)
  • 能力边界、风险和不适用场景
  • 现有能力与待开发设想必须明确分开
  • 如果目标行业、商业模式或业务指标无法从仓库判断,标注「待补充:需业务负责人确认」

docs/ARCHITECTURE.md

  • 模块/包的划分和职责
  • 依赖方向规则(哪层能引用哪层)
  • 主要数据流
  • 不要写实现细节,写"是什么"和"为什么这样分"

docs/CONVENTIONS.md

  • 文件命名规则
  • 变量/函数/类命名规则
  • 目录组织规则
  • 注释风格
  • 任何团队约定俗成的习惯

docs/TECH_DECISIONS.md

  • 为什么选这个框架而不是其他
  • 为什么用这个库
  • 历史上做过的重要架构决定和原因
  • 如果扫描时无法判断原因,写"待补充"并注明这是需要人工填写的

docs/QUALITY.md

  • 一个功能算"完成"的标准(Definition of Done)
  • 代码审查检查清单
  • 测试覆盖要求
  • 性能基准(如果有)

docs/exec-plans/backlog.md

  • 已知但尚未排期的待开发功能列表,这一点可以向用户询问
  • 每条格式:[优先级: P1/P2/P3] 功能描述 — 背景说明
  • 注意:backlog 是"想做但还没做",不是技术债务(技术债务是"已有但做得不好")
  • 如果扫描时发现后端已实现但前端未上线的功能、或文档中提到的计划中功能,写入此处
  • 如果扫描时没有发现明显的 backlog,写空列表并注明"待发现时补充"

docs/exec-plans/tech-debt-tracker.md

  • 已知的技术债务列表(现有代码中质量不佳、需要改进的部分)
  • 每条格式:[优先级] 问题描述 — 影响范围
  • 注意:不要把 backlog(待开发功能)混入此文件
  • 如果扫描时没有发现明显债务,写空列表并注明"待发现时补充"

质量检验

生成完成后,自检以下问题:

  • AGENTS.md 是否控制在 150 行以内?
  • AGENTS.md 里是否有具体的启动/测试命令(而非"见文档")?
  • business-solution.md 是否说明了服务谁、解决什么问题、如何产生价值和能力边界?
  • business-solution.md 是否将现有能力与潜在二开设想明确分开?
  • docs/ 里的文件是否有实际内容,而非空占位符?
  • TECH_DECISIONS.md 里无法判断的决策是否标注了"待补充"?
  • 目录表里的每个链接是否对应实际存在的文件?

完成后告知用户

输出一个简短摘要:

  1. 创建了哪些文件
  2. 提取出的业务定位、目标用户和主要解决方案
  3. 哪些内容是从项目扫描中推断的(可能需要人工核实)
  4. 哪些字段需要用户手动补充(标注了"待补充"的地方)
  5. 下一步:运行 harness-step2-fill-docs 深度验证业务能力和技术知识库

© simbajigege, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files in skills/harness-step1-create-agent-md of simbajigege/book2skills.

  • SKILL.md
  • LICENSE
  • README.md
  • en/harness-step1-create-agent-md.md
  • examples/en.yaml
  • examples/zh.yaml
  • zh/harness-step1-create-agent-md.md

Open the folder on GitHubat commit e5ba66c

Compare with similar skills

Harness Step1 Create Agents Md next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Harness Step1 Create Agents Md compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Harness Step1 Create Agents Md this skillsimbajigege/book2skills183—~1.1kAutomated safety check: PassApache-2.0
Create Agentprassanna-ravishankar/repowire264—~388Automated safety check: PassNone
Omnigent Knowledge Baseomnigent-ai/omnigent11k—~3.4kAutomated safety check: PassApache-2.0
Forge Agent Creatortailcallhq/forgecode7.6k—~7.3kAutomated safety check: PassApache-2.0
Agent Self-Customizationnanocoai/nanoclaw31k—~1.5kAutomated safety check: NotesMIT
Agents Md Generatorjulianromli/opencode-template144—~1.4kAutomated safety check: NotesNone

Similar skills

  • Create Agent

    prassanna-ravishankar/repowire

    A skill your agent uses when creating, updating, or explaining a standing Repowire agent folder, worker folder, durable-job executor context, or reusable agent-specific AGENTS.md guidance.

    264 GitHub stars~388 tokensUpdated yesterday
    Agent WorkflowsAuto-check passed
  • Omnigent Knowledge Base

    omnigent-ai/omnigent

    Reference for the Omnigent agent platform: agent directory layout, config.yaml fields, executor types, harness options, AGENTS.md and skill structure.

    11k GitHub stars~3.4k tokensUpdated today
    Agent WorkflowsAuto-check passed
  • Forge Agent Creator

    tailcallhq/forgecode

    Guides creating and editing custom agents for the code-forge application as Markdown files with YAML frontmatter in the project's .forge/agents folder.

    7.6k GitHub stars~7.3k tokensUpdated today
    Agent WorkflowsAuto-check passed
  • Agent Self-Customization

    nanocoai/nanoclaw

    A decision tree for an agent changing its own setup: edit memory directly, request approval for packages and MCP servers, and delegate code edits to a builder agent.

    31k GitHub stars~1.5k tokensUpdated today
    Agent WorkflowsAuto-check: notes
  • Agents Md Generator

    julianromli/opencode-template

    Generate hierarchical AGENTS.md structures for codebases. An agent skill from julianromli/opencode-template.

    144 GitHub stars~1.4k tokensUpdated 8 mo ago
    Agent WorkflowsAuto-check: notes
  • Toolkit

    notque/vexjoy-agent

    Toolkit management: create and evaluate skills and agents, manage routing tables, generate Claude.md.

    441 GitHub stars~3.1k tokensUpdated yesterday
    Agent WorkflowsAuto-check: notes

More from simbajigege/book2skills

All 37 skills in this repo
  • MEMORY.md Restructuring

    simbajigege/book2skills

    Reorganizes an overgrown MEMORY.md into a short pointer index plus separate topic files, and fixes or deletes outdated memories instead of archiving them.

    183 GitHub stars~2.4k tokensUpdated 1 mo ago
    Auto-check passed
  • Compact Memory Implementation

    simbajigege/book2skills

    A developer guide to adding compact memory to an agent: when to trigger compaction, how to fork a compactor sub-agent, what the summary holds, and how to restore it.

    183 GitHub stars~2.5k tokensUpdated 1 mo ago
    Auto-check passed
  • Semantic Line-Art SVG Diagrams

    simbajigege/book2skills

    Turns text, screenshots, or existing diagrams into minimal, accessible line-art SVGs for teaching material, with an optional Mermaid relationship spec.

    183 GitHub stars~2.5k tokensUpdated 1 mo ago
    Auto-check passed
  • Fail-Closed Agent Tool Builder

    simbajigege/book2skills

    Helps define agent tools with a fail-closed pattern: one class holding name, schema, security flags and a validate, permission and call execution chain.

    183 GitHub stars~2k tokensUpdated 1 mo ago
    Auto-check passed
  • LLM Query Loop Implementation

    simbajigege/book2skills

    Implements a production-style agent loop in your own AI product, with tool calling, tool results fed back, exit conditions and budget guards.

    183 GitHub stars~1.4k tokensUpdated 1 mo ago
    Auto-check passed
  • Tool Permission System Design

    simbajigege/book2skills

    Guides designing a layered permission pipeline for agent tools that decides which calls are allowed, need confirmation or are denied, with scopes and hooks.

    183 GitHub stars~2.1k tokensUpdated 1 mo ago
    Auto-check passed

Questions about Harness Step1 Create Agents Md

What does Harness Step1 Create Agents Md do?

Harness Engineering 第一阶段:扫描现有项目,生成 AGENTS.md(目录文件)和完整的 docs/ 知识库结构。. Harness Step1 Create Agents Md is an agent skill from simbajigege/book2skills.

When should I use Harness Step1 Create Agents Md?

Harness Step1 Create Agents Md fits situations like: tasks that involve Building AI agents; tasks that involve Agent instruction files.

How do I install Harness Step1 Create Agents Md in Claude Code?

Run `npx skills add simbajigege/book2skills --skill harness-step1-create-agents-md -a claude-code`. Or copy the skill folder (skills/harness-step1-create-agent-md in simbajigege/book2skills) into .claude/skills/harness-step1-create-agents-md in your project. Claude Code loads it when a task matches its description.

How do I install Harness Step1 Create Agents Md in Codex?

Run `npx skills add simbajigege/book2skills --skill harness-step1-create-agents-md -a codex`. Or copy the skill folder (skills/harness-step1-create-agent-md in simbajigege/book2skills) into .agents/skills/harness-step1-create-agents-md in your project. Codex loads it when a task matches its description.

Can I use Harness Step1 Create Agents Md in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add simbajigege/book2skills --skill harness-step1-create-agents-md -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/harness-step1-create-agents-md, .gemini/skills/harness-step1-create-agents-md, .github/skills/harness-step1-create-agents-md and .opencode/skills/harness-step1-create-agents-md in your project.

What does Harness Step1 Create Agents Md need to run?

SKILL.md names no scripts, command-line tools or credentials: Harness Step1 Create Agents Md is instructions for the agent only.

Does Harness Step1 Create Agents Md access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Harness Step1 Create Agents Md safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Harness Step1 Create Agents Md use?

Harness Step1 Create Agents Md is published under the Apache-2.0 licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Harness Step1 Create Agents Md use?

About 1.1k tokens (SKILL.md is roughly 4.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Harness Step1 Create Agents Md?

Skills that share tags, products or a category with Harness Step1 Create Agents Md: Create Agent (prassanna-ravishankar/repowire, 264 stars), Omnigent Knowledge Base (omnigent-ai/omnigent, 11k stars), Forge Agent Creator (tailcallhq/forgecode, 7.6k stars) and Agent Self-Customization (nanocoai/nanoclaw, 31k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Harness Step1 Create Agents Md?

simbajigege (a GitHub user) maintains it in simbajigege/book2skills, which has 183 GitHub stars. The repository holds 37 skills in this directory. The repository was last updated on August 26, 2026.

Source: simbajigege/book2skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.