tune-mjcf
Guidance for optimizing MuJoCo MJCF model files for simulation performance while maintaining numerical accuracy. This skill should be used when tuning physics simulation parameters, optimizing MuJoCo XML configurations, or balancing speed vs accuracy tradeoffs in robotics simulations.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install benchflow-ai-skillsbench-tune-mjcf
Repository
Skill path: registry/terminal_bench_2.0/letta_skills_batch/terminal_bench_2_0_tune-mjcf/environment/skills/tune-mjcf
Guidance for optimizing MuJoCo MJCF model files for simulation performance while maintaining numerical accuracy. This skill should be used when tuning physics simulation parameters, optimizing MuJoCo XML configurations, or balancing speed vs accuracy tradeoffs in robotics simulations.
Open repositoryBest for
Primary workflow: Ship Full Stack.
Technical facets: Full Stack.
Target audience: Development teams looking for install-ready agent workflows..
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: benchflow-ai.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install tune-mjcf into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/benchflow-ai/SkillsBench before adding tune-mjcf to shared team environments
- Use tune-mjcf for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.