Borrowing it
Nothing to install: this file belongs to Victory-7291/project-scaffold-setup-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Victory-7291/project-scaffold-setup-skills/main/AGENTS.mdgit clone --depth 1 https://github.com/Victory-7291/project-scaffold-setup-skillsWrote 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/instructions/victory-7291/project-scaffold-setup-skills/agents-md)<a href="https://agentmods.dev/instructions/victory-7291/project-scaffold-setup-skills/agents-md"><img src="https://agentmods.dev/badge/instructions/victory-7291/project-scaffold-setup-skills/agents-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/instructions/victory-7291/project-scaffold-setup-skills/agents-md"><img src="https://agentmods.dev/badge/instructions/victory-7291/project-scaffold-setup-skills/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00995 | $0.00995 |
| Opus 5 | $0.00498 | $0.00498 |
| Sonnet 5 | $0.00199 | $0.00199 |
| Haiku 4.5 | $0.00100 | $0.00100 |
Grade C, and why
project-scaffold-setup-skills AGENTS.md scanned grade C with 1 finding 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 9d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
rm -rf /tmp/codex-skill-smoke How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
本文件面向维护这个仓库的 agent。当前仓库专门保存项目脚手架类 skills,用来帮助 agent 从零快速构建不同类型的工程项目。
工作范围
- 主要内容在
skills/<skill-name>/。 - 每个 skill 至少包含
SKILL.md,通常还会包含scripts/、references/和agents/。 template/是新 skill 的起点,保持轻量,不要塞入某个具体技术栈的实现细节。
维护规则
- 修改某个 skill 前,先完整阅读该 skill 的
SKILL.md。 - 如果
SKILL.md指向references/或脚本,先读相关文件再动手。 - 保持每个 skill 的触发说明准确:
description应该说明适用场景,而不是只写一句泛泛介绍。 - 脚手架脚本优先使用 Python 标准库,避免引入不必要的运行时依赖。
- 生成脚本应支持明确的
--name和--out参数,必要时支持--force,但不要默认覆盖用户文件。 - 不要把大段生成模板复制进多个地方;如果逻辑复杂,优先集中在脚本或参考文档里维护。
- 不要提交生成出来的示例项目,除非它们是明确需要长期维护的 fixture。
文档风格
- README 面向使用者和贡献者,说明这个仓库是什么、有哪些 skills、如何新增和验证。
SKILL.md面向 agent,写可执行的判断和操作流程。references/*.md面向复杂背景和蓝图,可以比SKILL.md更详细。- 命令示例要能直接复制运行,路径尽量使用仓库相对路径。
- 避免只写抽象建议;需要给出默认工具链、目录结构、验证命令和失败处理方式。
新增或修改 Skill 的检查清单
SKILL.md有合法 frontmatter:name和description。description覆盖触发词、项目类型、核心工具链和使用时机。Workflow说明 greenfield 和 existing project 两种路径。Validation给出本地可以执行的验证命令。- 脚本可通过
python3 <script> --help。 - 脚本生成结果建议先放到
/tmp/<name>或其他临时目录检查。 - 如果新增
agents/openai.yaml,确保展示名、短描述和默认提示与 skill 名称一致。
推荐验证命令
检查 Python 脚本语法:
PYTHONPYCACHEPREFIX=/tmp/codex-pycache python3 -m py_compile skills/*/scripts/*.py
查看脚手架脚本参数:
python3 skills/cpp-project-setup/scripts/scaffold_cpp_project.py --help
python3 skills/embedded-project-setup/scripts/scaffold_embedded_project.py --help
python3 skills/python-fastapi-setup/scripts/scaffold_fastapi_project.py --help
生成临时项目做烟测:
rm -rf /tmp/codex-skill-smoke
mkdir -p /tmp/codex-skill-smoke
python3 skills/cpp-project-setup/scripts/scaffold_cpp_project.py \
--name smoke_cpp \
--out /tmp/codex-skill-smoke/smoke_cpp
python3 skills/embedded-project-setup/scripts/scaffold_embedded_project.py \
--name smoke_fw \
--out /tmp/codex-skill-smoke/smoke_fw
python3 skills/python-fastapi-setup/scripts/scaffold_fastapi_project.py \
--name smoke_api \
--out /tmp/codex-skill-smoke/smoke_api
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.
- 9d ago First seen · 82 lines · 995 tokens per session scan C bc723bfc69fe
project-scaffold-setup-skills AGENTS.md is an instructions file published in the GitHub repository Victory-7291/project-scaffold-setup-skills (7 stars, last pushed 1mo ago), licensed MIT. It adds 995 tokens to every session, about $0.0050 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.