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 commands/horizonrobotics/embodiedgen/processgit clone --depth 1 https://github.com/HorizonRobotics/EmbodiedGenWhat 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 | $0.00013 | $0.00188 |
| Opus 5 | $0.00006 | $0.00094 |
| Sonnet 5 | $0.00003 | $0.00038 |
| Haiku 4.5 | $0.00001 | $0.00019 |
Grade A, and why
process 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.
What it actually says
Process Skill Command
Route the user's request to the EmbodiedGen asset processing workflow.
Workflow
Step 1: Interpret the request
Use $ARGUMENTS if provided. If it is empty, ask for the URDF path and
desired scale factor and/or XYZ rotation in degrees.
Step 2: Load the skill
Use skill: "embodiedgen:asset-process".
Step 3: Execute the workflow
Follow the skill and build the correct
python -m embodied_gen.skills.asset-process.asset_process command.
Step 4: Deliver
Return:
- The exact command used
- The output path
- Whether the operation is normal mode or inplace mode
- The applied scale factor and XYZ rotation
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 · 33 lines · 13 tokens per session scan A 6a74355a5ff8
process is a command published in the GitHub repository HorizonRobotics/EmbodiedGen (648 stars, last pushed 9d ago), licensed Apache-2.0. It adds 13 tokens to every session and 188 once invoked, about $0.0001 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 commands, from other repositories
unity-placeholders
Generate placeholder sprites, 3D primitives, prefabs, and audio stubs for a Unity project so the game is visually testable before final assets exist.
combat-design
Design or revise combat rules, variables, readability, and tuning direction.
ui-flow-review
Review menus, HUD, navigation, and player flow from a UX perspective.
skyrun
Toggle the SKYRUN game pane in your terminal (free-play).
unity-optimize
Profile and optimize performance — uses MCP profiler for frame timing, memory, rendering stats. Identifies bottlenecks and applies fixes.
phaser-brainstorm
Shape a game idea into something buildable and correctly scoped.