Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add simbajigege/book2skills --skill harness-step1-create-agent-mdgit clone --depth 1 https://github.com/simbajigege/book2skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/simbajigege/book2skills/harness-step1-create-agent-md)<a href="https://agentmods.dev/skills/simbajigege/book2skills/harness-step1-create-agent-md"><img src="https://agentmods.dev/badge/skills/simbajigege/book2skills/harness-step1-create-agent-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/simbajigege/book2skills/harness-step1-create-agent-md"><img src="https://agentmods.dev/badge/skills/simbajigege/book2skills/harness-step1-create-agent-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00153 | $0.02375 |
| Opus 5 | $0.00077 | $0.01188 |
| Sonnet 5 | $0.00031 | $0.00475 |
| Haiku 4.5 | $0.00015 | $0.00237 |
Grade A, and why
harness-step1-create-agents-md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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:
# 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:
# [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)
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 207 lines · 153 tokens per session scan A 625203e5f82a
harness-step1-create-agents-md is a skill published in the GitHub repository simbajigege/book2skills (163 stars, last pushed 17d ago), licensed MIT. It adds 153 tokens to every session and 2,375 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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