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 astordu/qoderharness --skill agents-md-slimgit clone --depth 1 https://github.com/astordu/qoderharnessWrote 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/astordu/qoderharness/agents-md-slim)<a href="https://agentmods.dev/skills/astordu/qoderharness/agents-md-slim"><img src="https://agentmods.dev/badge/skills/astordu/qoderharness/agents-md-slim.svg" alt="Measured on agentmods" 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 | $0.00066 | $0.01379 |
| Opus 5 | $0.00033 | $0.00690 |
| Sonnet 5 | $0.00013 | $0.00276 |
| Haiku 4.5 | $0.00007 | $0.00138 |
Grade A, and why
agents-md-slim 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 7d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
精简 AGENTS.md 内容
AGENTS.md 在每次请求时都会被完整加载,因此必须精简。本 skill 遵循三条精简原则。
三条精简原则
原则一:控制指令预算
AGENTS.md 应尽可能小。每一条信息都要占用 token 并与任务指令竞争注意力。
应保留:
- 一句话项目描述
- 包管理器(非 npm 时必须注明)
- 非标准的构建/类型检查命令
- 真正与每个任务都相关的全局约定
应移除的过度细节:
- 详细的路径表格、架构清单 → 压缩为一句话能力描述
- 多行展开的组件列表 → 合并为单行概括
- 重复说明的调用链路 → 保留方向,去掉冗余前缀
判断标准:如果移除某条信息后 Agent 仍能通过阅读代码自行理解,则该信息属于过度细节。
原则二:描述能力,而非路径
文件路径是 AGENTS.md 中最容易过时的内容。路径重命名或文件移动后,AGENTS.md 就会变成误导信息。
禁止:
- 列出具体文件路径,如
app/api/routes/<指标>.py - 引用具体函数名,如
calc_trend() 函数 - 描述文件组织结构的表格中包含路径列
应该:
- 描述能力和职责,如"Routes 解析请求并委派 Service"
- 描述组织模式,如"按指标名分文件组织"
- 描述整体形状,让 Agent 自己探索定位
原则三:移除 Agent 可自行发现的信息
不要把 Agent 阅读代码就能知道的信息写进 AGENTS.md。
应移除的冗余信息:
- 语言/框架标准模式(如"每层通过
__init__.py统一导出") - 代码级实现细节(如"Service 使用静态方法")
- 配置级细节(如"数据库为 SQLite,启动时通过
Base.metadata.create_all()自动建表") - 框架默认行为(如"所有 API 调用均为带类型的函数")
应保留的关键信息:
- 非显而易见的架构约定(如"修改数据结构时前后端类型必须同步更新")
- 与标准做法的偏离(如"包管理器为 uv 而非 pip")
- Agent 无法从代码推断的隐式约定(如"CORS 仅配置了 localhost:5173")
执行步骤
1. 逐条审查
读取现有 AGENTS.md,对每一条信息判断:
- 是否包含文件路径?→ 原则二
- 是否为 Agent 可自行发现的信息?→ 原则三
- 是否为过度细节?→ 原则一
2. 提出修改建议
对标记为问题的内容,用能力描述替换路径引用,用简洁概括替换冗长细节。将修改建议列出,等待用户确认后再修改。
3. 验证
确认修改后的 AGENTS.md:
- 不包含具体文件路径
- 不包含 Agent 可自行发现的信息
- 描述简洁,每节尽量用一句话概括
示例
示例 1:路径表格 → 能力描述
Before:
| 层级 | 路径 | 职责 |
|------|------|------|
| Routes | `app/api/routes/<指标>.py` | FastAPI 路由,解析请求,委派给 Service |
| DTOs | `app/api/dtos/<指标>.py` | Pydantic 模型,负责请求/响应序列化 |
| Services | `app/services/<指标>.py` | 业务逻辑层,调用 Repo 并转换为 DTO |
| Repos | `app/db/repos/<指标>.py` | 数据访问层,封装 SQLAlchemy 查询 |
| Models | `app/db/models/<指标>.py` | SQLAlchemy ORM 表定义 |
After: 每项健康指标在各层都遵循相同模式:Routes 解析请求并委派 Service,DTOs 负责序列化,Services 处理业务逻辑,Repos 封装数据查询,Models 定义 ORM 表。按指标名分文件组织。
示例 2:文件清单 → 一句话概括
Before:
- `src/api/client.ts` - 集中式 axios 客户端,所有 API 调用均为带类型的函数
- `src/types/health.ts` - TypeScript 接口,与后端 Pydantic DTO 一一对应
- `src/hooks/useHealthData.ts` - 自定义 Hook,通过 `Promise.all` 并行拉取所有指标数据
- `src/components/DashboardGrid.tsx` - 编排组件,将数据分发给各指标卡片
- `src/components/<指标>Card.tsx` - 每个指标一个卡片组件,通过 props 接收数据
- `src/components/TrendChart.tsx` - 共享的 recharts 折线图组件,被各卡片复用
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.
- 7d ago First seen · 122 lines · 66 tokens per session scan A e337e5abf9ee
agents-md-slim is a skill published in the GitHub repository astordu/qoderharness (24 stars, last pushed 4d ago), licensed MIT. It adds 66 tokens to every session and 1,379 once invoked, about $0.0003 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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