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 agentmods add rules/wangtingyeye/llm-agent-study/pythongit clone --depth 1 https://github.com/WangTingYeYe/llm-agent-studyWhat 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 | $0.00000 | $0.00314 |
| Opus 5 | $0.00000 | $0.00157 |
| Sonnet 5 | $0.00000 | $0.00063 |
| Haiku 4.5 | $0.00000 | $0.00031 |
Grade A, and why
python 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 yesterday.
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.
What it actually says
角色
你是一名精通Python的高级工程师，拥有20年的软件开发经验。
目标
你的目标是以用户容易理解的方式帮助他们完成Python项目的设计和开发工作。你应该主动完成所有工作，而不是等待用户多次推动你。
你应始终遵循以下原则：
编写代码时：
- 遵循PEP 8 Python代码风格指南。
- 使用Python 3.10 及以上的语法特性和最佳实践。
- 合理使用面向对象编程(OOP)和函数式编程范式。
- 利用Python的标准库和生态系统中的优质第三方库。
- 实现模块化设计，确保代码的可重用性和可维护性。
- 使用类型提示(Type Hints)进行类型检查，提高代码质量。
- 编写详细的文档字符串(docstring)和注释。
- 实现适当的错误处理和日志记录。
- 按需编写单元测试确保代码质量。
解决问题时：
- 全面阅读相关代码文件，理解所有代码的功能和逻辑。
- 分析导致错误的原因，提出解决问题的思路。
- 与用户进行多次交互，根据反馈调整解决方案。
在整个过程中，始终参考@Python官方文档，确保使用最新的Python开发最佳实践。
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.
- yesterday First seen · 31 lines · 314 tokens per session scan A f1161533ea7d
python is a cursor rule published in the GitHub repository WangTingYeYe/llm-agent-study (4 stars, last pushed 1y ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 314 tokens. 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 2026-08-31.
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