Check Inference

What it does

When your agent uses it

• Asks to check inference
• Test inference server
• Verify policy server
• Provides an IP/port and wants to confirm a servepolicy / WebSocket inference server is working before running benchmarks

Example prompts

• “s checkinference.py. Trigger: When the user asks to”
• “校验模型推理”
• “test inference server”
• “/check-inference”

Requirements

• Python 3

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

1. 1Loads the payload.
2. 2Connects to the WebSocket server using msgpack-numpy.
3. 3Sends one request, receives one action chunk.
4. 4Validates: schema (key presence), per-dim min/max/mean/std, NaN/Inf flags, out-of-range checks (kind-aware: JOINT_ABS in radians, EEF_ABS…

What it can do on your machine

Read from SKILL.md and the folder at commit 6ca11c7. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • python3

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Check Inference loads about 1.4k tokens when it runs. Until then it costs about 119 tokens; SKILL.md has 517 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~119

When it runs · the whole SKILL.md, loaded when a task matches

~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from AgibotTech/genie_sim at commit 6ca11c7, republished under its MPL-2.0 licence (© AgibotTech). 517 words, ~1,399 tokens.

name

check-inference

description

Probe a model inference WebSocket server (e.g. `serve_policy`) and validate the response — using the `geniesim benchmark check-inference` CLI verb, which wraps the benchmark package's `check_inference.py`. Trigger: When the user asks to "check inference", "校验模型推理", "test inference server", "verify policy server", "ping the model", or provides an IP/port and wants to confirm a serve_policy / WebSocket inference server is working before running benchmarks.

license

MPL-2.0

metadata.author

genie-sim

metadata.version

2.0

prerequisites

geniesim_cli:fresh-machine-setup

# Bundled payload — just point it at the server
geniesim benchmark check-inference --infer-host=<HOST>:<PORT>

# Override with your own payload (positional)
geniesim benchmark check-inference debug_preview/debug_0001.pkl \
    --host <HOST> --port <PORT>

© AgibotTech, MPL-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in source/geniesim_benchmark/skills/check-inference of AgibotTech/genie_sim.

Open the folder on GitHubat commit 6ca11c7