general

General project rules covering Python, Poetry dependency management, GitHub Actions, Bash scripts, code style, project structure, testing, and maintainability.

In plain words
What is it for?
Use it as a baseline when developing or reviewing a Python project that uses Poetry, GitHub, GitHub Actions, and Bash.
Why use it?
It records shared project expectations so development work follows the same structure and practices. It also specifies that responses should be in Chinese.

Cursor rule for Cursor

Install

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.

agentmods
npx agentmods add rules/wangtingyeye/llm-agent-study/general
Clone the repo
git clone --depth 1 https://github.com/WangTingYeYe/llm-agent-study

Made for: Cursor.

Per session 291 This file is loaded in full into every session.
When invoked 291 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00291 $0.00291
Opus 5 $0.00146 $0.00146
Sonnet 5 $0.00058 $0.00058
Haiku 4.5 $0.00029 $0.00029

Measured 2d ago against content hash 10511f82aec8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 2d 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.

.cursor/rules/backup/python/general.mdc · 42 lines

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
Changes

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.

  1. 2d ago First seen · 42 lines · 291 tokens per session scan A 10511f82aec8

Subscribe to this mod's changes

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 $0.0015 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 2026-08-31.