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.
npx agentmods add instructions/nvlabs/simfoundry/agents-mdgit clone --depth 1 https://github.com/NVlabs/SimFoundryWhat 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 | $0.04224 | $0.04224 |
| Opus 5 | $0.02112 | $0.02112 |
| Sonnet 5 | $0.00845 | $0.00845 |
| Haiku 4.5 | $0.00422 | $0.00422 |
Grade A, and why
SimFoundry 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.
How it starts
The opening of the file, as written. The whole thing — 307 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SimFoundry — agent guide
Orientation for coding agents. This covers what the code does not say out loud: which environment to run in, which trees are safe to edit, and which contracts break silently. For what the project is, read README.md.
What this repo does
SimFoundry turns a short real-world video into a physics-ready OmniGibson scene: segment
the objects, reconstruct geometry, generate textured meshes, compile a scene with physical
parameters and task proposals. The pipeline runs in three stages under
scripts/pipeline/:
| Stage | Directory | Produces |
|---|---|---|
| A — reconstruction | A_reconstruction/stages/ |
Depth, segmentation, meshes, s11_sim/scene_objects_info.json, s12_physics/pb_scene_poses.json, an OmniGibson scene |
| B — augmentation | B_augmentation/stages/ |
Digital-cousin variants, scene sampling, task proposals |
| C — application | C_application/stages/ |
Teleop, demo generation, policy evaluation |
Scene editing sits between B and C: a human corrects what the pipeline got wrong — object poses, scales, cameras — before the scene is used for learning or evaluation. Everything downstream inherits those corrections.
Environments
There are many conda envs on a dev box (3dgrut, da3, hunyuan, …); most belong to a
single pipeline stage. For general work:
simfoundry— the main env. OmniGibson, Isaac Sim, torch. Used by the pipeline, the OmniGibson editor, andsettle.py.find_settle_pythoninlight_editor/server.pychecks that the env'somnigibsonresolves inside this repo.simfoundry-editor— the light editor's env, no GPU. Created byscripts/installation/install_light_editor.sh; re-run that after a pull. See the trap below.
Trap:
omnigibsoncan resolve outside this checkout. An env may carry this repo'ssimfoundrypackage but a different clone's OmniGibson. The editor then runs against the wrongdeps/tree and stamps the wrong OmniGibson version into saved scenes.run_editor.shwarns about this at startup; do not ignore it. Check withpython -c 'import omnigibson; print(omnigibson.__file__)'.
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.
- 2d ago First seen · 307 lines · 4,224 tokens per session scan A 3e876c469e0f
SimFoundry AGENTS.md is an instructions file published in the GitHub repository NVlabs/SimFoundry (290 stars, last pushed 6d ago), licensed Apache-2.0. It adds 4,224 tokens to every session, about $0.0211 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.
Other instructions, from other repositories
wisp-science AGENTS.md
AGENTS.md instructions for xuzhougeng/wisp-science, covering agents.md, project orientation, repository layout, engineering rules and verification commands.
MoleCode AGENTS.md
Instructions for AtomFlow-AI/MoleCode, covering agents.md — molecode, what this repo is, use the molecode skill, molecode-first rule and cli quick start.
relarena CLAUDE.md
Instructions for PriorLabs/relarena: All package notes live in AGENTS.md — read that first.
ami-mcp CLAUDE.md
Claude Code instructions for kratsg/ami-mcp, covering ami-mcp — contributor guide, architecture, project layout, tool registration pattern and tools/mymodule.py.
symkit-mcp CLAUDE.md
Instructions for LBurny/symkit-mcp, covering claude.md - claude code project guide, project overview, core tools, usage patterns and stateless quick calculation.
arxiv-wiki AGENTS.md
AGENTS.md instructions for synabreu/arxiv-wiki, covering agents.md, project goal and rules.