evaluating-cosmos-policy SKILL.md skillA
evaluating-cosmos-policy from orchestra-research/ai-research-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
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- Audit grade
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- SKILL.md skill
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- orchestra-research/ai-research-skills
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18-multimodal/cosmos-policy/SKILL.md- Versions recorded
- 5
- Latest version
- v1.0.0, committed Mar 17, 2026
- First version recorded
- Mar 17, 2026
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- 14,606 bytes
- Repository stars
- 13,718
- License
- MIT
Evaluates NVIDIA Cosmos Policy on LIBERO and RoboCasa simulation environments. Use when setting up cosmos-policy for robot manipulation evaluation, running headless GPU evaluations with EGL rendering, or profiling inference latency on cluster or local GPU machines.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Cosmos Policy Evaluation
Evaluation workflows for NVIDIA Cosmos Policy on LIBERO and RoboCasa simulation environments from the public `cosmos-policy` repository. Covers blank-machine setup, headless GPU evaluation, and inference profiling.
## Quick start
Run a minimal LIBERO evaluation using the official public eval module:
```bash
uv run --extra cu128 --group libero --python 3.10 \
python -m cosmos_policy.experiments.robot.libero.run_libero_eval \
--config cosmos_predict2_2b_480p_libero__inference_only \
--ckpt_path nvidia/Cosmos-Policy-LIBERO-Predict2-2B \
--config_file cosmos_policy/config/config.py \
--use_wrist_image True \
--use_proprio True \
--normalize_proprio True \
--unnormalize_actions True \
--dataset_stats_path nvidia/Cosmos-Policy-LIBERO-Predict2-2B/libero_dataset_statistics.json \
--t5_text_embeddings_path nvidia/Cosmos-Policy-LIBERO-Predict2-2B/libero_t5_embeddings.pkl \
--trained_with_image_aug True \
--chunk_size 16 \
--num_open_loop_steps 16 \
--task_suite_name libero_10 \
--num_trials_per_task 1 \
--local_log_dir cosmos_policy/experiments/robot/libero/logs/ \
--seed 195 \
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How to install
mdr add orchestra-research/ai-research-skills/evaluating-cosmos-policy@sha256:31d6b4701fae46b0The line at the top of this page pins the label v1.0.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_q6tmnqwn4asan32m)
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Versions
The registry has recorded 5 versions of this file, all committed on Mar 17, 2026.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.0.0 latest | 2026-03-17 | 03ec530 | 14,606 B | A | view · diff |
| v1.0.0 | 2026-03-17 | 3a10c79 | 14,057 B | A | view · diff |
| v1.0.0 | 2026-03-17 | a79c5d6 | 14,783 B | A | view · diff |
| v1.0.0 | 2026-03-17 | ffb156a | 14,635 B | A | view · diff |
| v1.0.0 | 2026-03-17 | 97c8398 | 14,477 B | A | view |
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Source
orchestra-research/ai-research-skills · 13,718 stars · license MIT · pushed 2026-10-11 · branch main
API
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