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.
git clone --depth 1 https://github.com/WangTingYeYe/llm-agent-studyWrote 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/rules/wangtingyeye/llm-agent-study/general)<a href="https://agentmods.dev/rules/wangtingyeye/llm-agent-study/general"><img src="https://agentmods.dev/badge/rules/wangtingyeye/llm-agent-study/general/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/rules/wangtingyeye/llm-agent-study/general"><img src="https://agentmods.dev/badge/rules/wangtingyeye/llm-agent-study/general.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 | $0.00291 | $0.00291 |
| Opus 5.5 | $0.00116 | $0.00116 |
| Sonnet 5.5 | $0.00058 | $0.00058 |
| Haiku 4.5 | $0.00029 | $0.00029 |
Grade A, and why
general 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 1mo 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.
This is a copy
100% identical to general — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
项目通用规范
技术栈
- Python 3.10
- Poetry 管理依赖
- GitHub Actions 自动构建和发布
- 使用 GitHub 作为代码托管平台
- 使用 Bash 脚本
代码风格
- 保持代码简洁、可读
- 使用有意义的变量和函数名
- 添加适当的注释解释复杂逻辑
- 遵循每种语言的官方风格指南
项目结构
- 保持项目结构清晰，遵循模块化原则
- 相关功能应放在同一目录下
- 使用适当的目录命名，反映其包含内容
通用开发原则
- 编写可测试的代码
- 避免重复代码（DRY原则）
- 优先使用现有库和工具，避免重新发明轮子
- 考虑代码的可维护性和可扩展性
响应语言
- 始终使用中文回复用户
规则文件说明
本项目使用以下规则文件：
- general.mdc：通用规范（本文件）
- python.mdc：Python开发规范
- document.mdc：文档规范
- git.mdc：Git提交规范
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.
- 1mo ago First seen · 42 lines · 291 tokens per session scan A 10511f82aec8
general is a cursor rule published in the GitHub repository WangTingYeYe/llm-agent-study (4 stars, last pushed 1y ago), licensed MIT. It adds 291 tokens to every session, about $0.0012 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to general, differing in 0 lines, and is treated as a copy.
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