pytorch

A Cursor rule set for writing PyTorch code, where PyTorch is a software library for building and training machine-learning models.

In plain words
What is it for?
It helps with directory layouts, file names, module organization, and other PyTorch coding practices.
Why use it?
It gives the coding assistant shared standards for organizing PyTorch code instead of leaving structure and naming decisions unclear.

Cursor rule

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/bhartendu-kumar/rules_template/pytorch
Clone the repo
git clone --depth 1 https://github.com/Bhartendu-Kumar/rules_template
Per session 0 Nothing until a file matches its globs; then the whole rule loads.
When invoked 4,770 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00000 $0.04770
Opus 5 $0.00000 $0.02385
Sonnet 5 $0.00000 $0.00954
Haiku 4.5 $0.00000 $0.00477

Measured 2d ago against content hash 649444e348b5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pytorch 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.

specific_rule_files/pytorch.mdc · 386 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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 · 386 lines · 0 tokens per session scan A 649444e348b5

Subscribe to this mod's changes

pytorch is a cursor rule published in the GitHub repository Bhartendu-Kumar/rules_template (1,059 stars, last pushed 1y ago), with no licence file. It costs nothing until one of its globs matches a file; then it loads 4,770 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 2026-08-30.