awesome-cursor-rules-mdc is a generator that creates Cursor MDC rule files from structured library information, using semantic search and language models to gather and organize guidance. Developers use it to produce reusable rules for libraries in Cursor, and the catalogue includes 200 of those rules.
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/sanjeed5/awesome-cursor-rules-mdcWrote 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/sanjeed5/awesome-cursor-rules-mdc/pylint)<a href="https://agentmods.dev/rules/sanjeed5/awesome-cursor-rules-mdc/pylint"><img src="https://agentmods.dev/badge/rules/sanjeed5/awesome-cursor-rules-mdc/pylint/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/sanjeed5/awesome-cursor-rules-mdc/pylint"><img src="https://agentmods.dev/badge/rules/sanjeed5/awesome-cursor-rules-mdc/pylint.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 | $0.01912 | $0.01912 |
| Opus 5 | $0.00956 | $0.00956 |
| Sonnet 5 | $0.00382 | $0.00382 |
| Haiku 4.5 | $0.00191 | $0.00191 |
Grade A, and why
pylint 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 249 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pylint Best Practices
Pylint is our go-to for deep semantic analysis and identifying complex code smells in Python. While Ruff handles fast style checks and MyPy ensures type correctness, Pylint focuses on broader architectural and logical issues. This guide ensures Pylint is a powerful, not noisy, part of our workflow.
1. Configuration is King: pyproject.toml
Always use pyproject.toml for Pylint configuration. This ensures consistency across all environments and developers.
Action: Generate a baseline config and commit it.
pylint --generate-toml-config > pyproject.toml
1.1. Silence the Noise, Enable What Matters
Pylint is notoriously noisy by default. Start by disabling everything and selectively enabling relevant categories. Focus on convention, refactor, warning, and error for semantic checks.
❌ BAD: Default Pylint output (overwhelming)
pylint your_module.py # Flooded with style and minor issues
✅ GOOD: Targeted Pylint checks in pyproject.toml
# pyproject.toml
[tool.pylint.main]
disable = "all"
enable = [
"convention",
"refactor",
"warning",
"error",
# Add specific messages if needed, e.g., "W0611", "R0913"
]
1.2. Filter by Confidence
Reduce false positives by only showing warnings with high confidence.
✅ GOOD: Filter low-confidence warnings in pyproject.toml
# pyproject.toml
[tool.pylint.main]
confidence = ["HIGH", "CONTROL_FLOW"] # Focus on reliable detections
2. Code Organization & Readability
Pylint helps enforce structural best practices beyond basic style.
2.1. Docstrings for Everything
Every module, class, and function must have a docstring. Pylint enforces this.
❌ BAD: Missing docstrings
def calculate_sum(a, b):
return a + b
✅ GOOD: Clear and concise docstrings
"""This module provides basic arithmetic operations."""
def calculate_sum(a: int, b: int) -> int:
"""
Calculates the sum of two integers.
:param a: The first integer.
:param b: The second integer.
:return: The sum of a and b.
"""
return a + b
Pylint messages: C0114 (module), C0115 (class), C0116 (function/method)
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.
- 6d ago First seen · 249 lines · 1,912 tokens per session scan A 55f06d9758fd
pylint is a cursor rule published in the GitHub repository sanjeed5/awesome-cursor-rules-mdc (3,570 stars, last pushed 3mo ago), licensed CC0-1.0. It adds 1,912 tokens to every session, about $0.0096 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 2026-09-03.
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