Individual skill
evaluating-cosmos-policy
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.
plugins/KalarisLabs/research-agent-skills/skills/evaluating-cosmos-policy/SKILL.md
Source commit d780783eba4ecc7c8b9429f95c9362df95f07c61
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Network or broad shell
- Last checked
- Nov 4, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 1,532
- Repository last updated
- Nov 6, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai-coding Repository topic
- awesome Repository topic
- awesome-list Repository topic
- codex Repository topic
- codex-plugins Repository topic
- openai Repository topic
- codex-skill Repository topic
- codex-skills Repository topic
- marketplace Repository topic
- codex-marketplace Repository topic
- engineering Derived category
Declared tags are partial or unavailable.
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
SKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesSKILL.mdcore · 16,853 bytesreferences/libero-commands.mddoc · 6,863 bytesreferences/robocasa-commands.mddoc · 5,894 bytes
Read excerpt
# 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 \