linux-nvidia-cuda-python-cursorrules-prompt-file

linux-nvidia-cuda-python-cursorrules-prompt-file is a cursor rule for Cursor from PatrickJS/awesome-cursorrules. It costs 460 tokens per session, scanned A, original, CC0-1.0.

Project rules for a Linux pipeline that downloads machine-learning models, reduces their size through quantization, and uploads them to a Hugging Face-compatible repository. It includes Python, Bash, NVIDIA CUDA, and AMD ROCm considerations.

In plain words
What is it for?
Use it when developing or documenting model-quantization tools that run on Linux with NVIDIA or AMD GPUs.
Why use it?
It keeps the setup and processing steps focused on supported Linux hardware and encourages clear handling of model or GPU compatibility errors.

Cursor rule for Cursor

Written for Cursor: a Cursor rule (.mdc). Also seen: mentions Cursor.

About the project

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.

PatrickJS/awesome-cursorrules · 40,728 stars · on GitHub

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/patrickjs/awesome-cursorrules/linux-nvidia-cuda-python-cursorrules-prompt-file
Clone the repo
git clone --depth 1 https://github.com/PatrickJS/awesome-cursorrules

Made for: Cursor.

Wrote 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.

agentmods badge for linux-nvidia-cuda-python-cursorrules-prompt-file

README.md
[![agentmods](https://agentmods.dev/badge/rules/patrickjs/awesome-cursorrules/linux-nvidia-cuda-python-cursorrules-prompt-file.svg)](https://agentmods.dev/rules/patrickjs/awesome-cursorrules/linux-nvidia-cuda-python-cursorrules-prompt-file)
Your own site
<a href="https://agentmods.dev/rules/patrickjs/awesome-cursorrules/linux-nvidia-cuda-python-cursorrules-prompt-file"><img src="https://agentmods.dev/badge/rules/patrickjs/awesome-cursorrules/linux-nvidia-cuda-python-cursorrules-prompt-file.svg" alt="Measured on agentmods" height="20"></a>
Per session 460 This file is loaded in full into every session.
When invoked 460 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 5.1 $0.00460 $0.00460
Opus 5 $0.00230 $0.00230
Sonnet 5 $0.00092 $0.00092
Haiku 4.5 $0.00046 $0.00046

Measured 2d ago against content hash 155da3375757, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

linux-nvidia-cuda-python-cursorrules-prompt-file 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.

rules/linux-nvidia-cuda-python-cursorrules-prompt-file.mdc · 32 lines

What it actually says

  1. Project Overview:

  - App Name: 'srt-model-quantizing'  

  • Developer: SolidRusT Networks  
  • Functionality: A pipeline for downloading models from Hugging Face, quantizing them, and uploading them to a Hugging Face-compatible repository.  
  • Design Philosophy: Focused on simplicity—users should be able to clone the repository, install dependencies, and run the app using Python or Bash with minimal effort.  
  • Hardware Compatibility: Supports both Nvidia CUDA and AMD ROCm GPUs, with potential adjustments needed based on specific hardware and drivers.  
  • Platform: Intended to run on Linux servers only.
  1. Development Principles:

  - Efficiency: Ensure the quantization process is streamlined, efficient, and free of errors.  

  • Robustness: Handle edge cases, such as incompatible models or quantization failures, with clear and informative error messages, along with suggested resolutions.  
  • Documentation: Keep all documentation up to date, including the README.md and any necessary instructions or examples.
  1. AI Agent Alignment:

  - Simplicity and Usability: All development and enhancements should prioritize maintaining the app's simplicity and ease of use.  

  • Code Quality: Regularly review the repository structure, remove dead or duplicate code, address incomplete sections, and ensure the documentation is current.  
  • Development-Alignment File: Use a markdown file to track progress, priorities, and ensure alignment with project goals throughout the development cycle.
  1. Continuous Improvement:

  - Feedback: Actively seek feedback on the app's functionality and user experience.  

  • Enhancements: Suggest improvements that could make the app more efficient or user-friendly, ensuring any changes maintain the app's core principles.  
  • Documentation of Changes: Clearly document any enhancements, bug fixes, or changes made during development to ensure transparency and maintainability.
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 · 32 lines · 460 tokens per session scan A 155da3375757

Subscribe to this mod's changes

linux-nvidia-cuda-python-cursorrules-prompt-file is a cursor rule published in the GitHub repository PatrickJS/awesome-cursorrules (40,728 stars, last pushed 3mo ago), licensed CC0-1.0. It adds 460 tokens to every session, about $0.0023 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.