nvalchemi-toolkit AGENTS.md

Repository instructions for NVIDIA Alchemi Toolkit, a Python framework for GPU-based atomic simulation and machine-learned materials workflows. They cover Python, CUDA, dependencies, testing, and contribution practices.

In plain words
What is it for?
Use it when developing simulations, atomic-data pipelines, model wrappers, training workflows, CUDA-related code, or pull requests.
Why use it?
They make the required development environment and repository checks clear, reducing setup errors and changes that fail project review.

Instructions file for CodexOpenCode

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 instructions/nvidia/nvalchemi-toolkit/agents-md
Clone the repo
git clone --depth 1 https://github.com/NVIDIA/nvalchemi-toolkit

Made for: Codex, OpenCode.

Per session 2,740 This file is loaded in full into every session.
When invoked 2,740 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 $0.02740 $0.02740
Opus 5 $0.01370 $0.01370
Sonnet 5 $0.00548 $0.00548
Haiku 4.5 $0.00274 $0.00274

Measured 2d ago against content hash 66db104387be, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

nvalchemi-toolkit AGENTS.md 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.

AGENTS.md · 233 lines

How it starts

The opening of the file, as written. The whole thing — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md - NVIDIA ALCHEMI Toolkit

Guidelines for AI coding agents operating in this repository.

Project Overview

nvalchemi-toolkit provides the nvalchemi Python package: a GPU-first framework for AI atomic simulation workflows. It covers graph-structured atomic data, model wrappers for machine-learned interatomic potentials, batched dynamics, hooks/reporting, and training/finetuning workflows.

  • Python support: >=3.11,<3.14; CI and setup examples use Python 3.12.
  • Package manager: uv; build backend: hatchling.
  • Core dependencies: PyTorch, Pydantic v2, jaxtyping, TensorDict, Zarr, Rich, PhysicsNeMo, and nvalchemi-toolkit-ops.
  • The project is in public beta. Public PRs may not be accepted immediately, but bug reports, feature requests, and scoped implementation discussions are welcome.

Repository Practices

  • Commits need DCO sign-off and Conventional Commits-style messages: git commit -s -m "fix: describe change". Pre-commit hooks are required; PRs that skip them are not expected to be reviewed. See CONTRIBUTING.md for DCO details, hook setup, and CI stages.
  • The PR template expects a short description, testing notes, changelog updates, docstring/docs updates where applicable, and the relevant type-of-change box.
  • Keep work tightly scoped; read docs/userguide/about/ before broad changes.

CUDA And Environment Setup

First check CUDA availability:

nvidia-smi
  • If nvidia-smi is missing or reports no usable device, use default uv commands without CUDA extras where possible.
  • If it reports CUDA 12.x, pass --extra cu12 to uv commands and CUDA_EXTRA=cu12 to make targets.
  • If it reports CUDA 13.x, cu13 is the default Makefile extra; explicit commands can still use --extra cu13 or CUDA_EXTRA=cu13.
  • Do not use uv sync --all-extras: the CUDA variants and some model extras are mutually exclusive.

Common setup commands:

# Default development environment; Makefile currently defaults CUDA_EXTRA=cu13.
make install

# CUDA 12 development environment.
make install CUDA_EXTRA=cu12

# Add CUDA-aligned optional extras, for example MACE.
make install CUDA_EXTRA=cu12 OPTIONAL_EXTRAS=mace

# Direct uv equivalents.
uv sync --extra cu13
uv sync --extra cu12 --extra mace

# Include documentation dependencies when needed.
uv sync --extra cu13 --group docs

Read the full file on GitHub · 233 lines

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 · 233 lines · 2,740 tokens per session scan A 66db104387be

Subscribe to this mod's changes

nvalchemi-toolkit AGENTS.md is an instructions file published in the GitHub repository NVIDIA/nvalchemi-toolkit (150 stars, last pushed 8d ago), licensed Apache-2.0. It adds 2,740 tokens to every session, about $0.0137 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 2026-08-30.