PatrickJS/awesome-cursorrules is a collection of Markdown rule files that give Cursor AI editor project-specific instructions about code, frameworks, workflows, and standards. Developers use it to find reusable guidance for shaping Cursor’s behavior in different kinds of software projects.
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/PatrickJS/awesome-cursorrulesWrote 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/patrickjs/awesome-cursorrules/python-cursorrules-prompt-file-best-practices)<a href="https://agentmods.dev/rules/patrickjs/awesome-cursorrules/python-cursorrules-prompt-file-best-practices"><img src="https://agentmods.dev/badge/rules/patrickjs/awesome-cursorrules/python-cursorrules-prompt-file-best-practices/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/patrickjs/awesome-cursorrules/python-cursorrules-prompt-file-best-practices"><img src="https://agentmods.dev/badge/rules/patrickjs/awesome-cursorrules/python-cursorrules-prompt-file-best-practices.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 | $0.00374 | $0.00374 |
| Opus 5.5 | $0.00150 | $0.00150 |
| Sonnet 5.5 | $0.00075 | $0.00075 |
| Haiku 4.5 | $0.00037 | $0.00037 |
Grade A, and why
python-cursorrules-prompt-file-best-practices 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- cursorrules — 86% identical, 14 lines differ
What it actually says
You are an AI assistant specialized in Python development. Your approach emphasizes:
- Clear project structure with separate directories for source code, tests, docs, and config.
- Modular design with distinct files for models, services, controllers, and utilities.
- Configuration management using environment variables.
- Robust error handling and logging, including context capture.
- Comprehensive testing with pytest.
- Detailed documentation using docstrings and README files.
- Dependency management via https://github.com/astral-sh/uv and virtual environments.
- Code style consistency using Ruff.
- CI/CD implementation with GitHub Actions or GitLab CI.
AI-friendly coding practices:
- You provide code snippets and explanations tailored to these principles, optimizing for clarity and AI-assisted development.
Follow the following rules:
- For any Python file, ALWAYS add typing annotations to each function or class. Include explicit return types (including None where appropriate). Add descriptive docstrings to all Python functions and classes.
- Please follow PEP 257 docstring conventions. Update existing docstrings as needed.
- Make sure you keep any comments that exist in a file.
- When writing tests, ONLY use pytest or pytest plugins (not unittest). All tests should have typing annotations. Place all tests under ./tests. Create any necessary directories. If you create packages under ./tests or ./src/<package_name>, be sure to add an init.py if one does not exist.
All tests should be fully annotated and should contain docstrings. Be sure to import the following if TYPE_CHECKING: from _pytest.capture import CaptureFixture from _pytest.fixtures import FixtureRequest from _pytest.logging import LogCaptureFixture from _pytest.monkeypatch import MonkeyPatch from pytest_mock.plugin import MockerFixture
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 · 33 lines · 374 tokens per session scan A 06aa5ceb6bd7
python-cursorrules-prompt-file-best-practices is a cursor rule published in the GitHub repository PatrickJS/awesome-cursorrules (40,970 stars, last pushed 4mo ago), licensed CC0-1.0. It adds 374 tokens to every session, about $0.0015 per session on Opus 5.5. 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 2026-09-03.
Other cursor rules, from other repositories
python-general-coding-standards
A set of general standards for Python projects, including type hints, input checking, code style, security, web requests, background work, and tests. It also covers FastAPI-specific tasks such as CORS and authentication.
pytest
You are an expert in pytest testing. Follow these rules.
rule-01
This is test rule number in the large package scalability test.
python
Python development guidelines — PEP 8, type hints, error handling, async patterns, packaging, and testing. Applied when working with Python code.
rule-02
This is test rule number in the large package scalability test.
rule-03
This is test rule number in the large package scalability test.