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Agent skill

Run Teleop

by AgibotTech in AgibotTech/genie_sim

Launch the geniesimteleop VR / Pico teleoperation loop (or the in-process image bridge) using the geniesim teleop CLI verb, typically inside the Genie Sim GUI Docker container.

MPL-2.0Auto-check passedDevOps & Cloud

Install Run Teleop

skills CLI
$ npx skills add AgibotTech/genie_sim --skill run-teleop -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install AgibotTech/genie_sim run-teleop --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/AgibotTech/genie_sim.git skills-src && mkdir -p .claude/skills && cp -r skills-src/source/geniesim_teleop/skills/run-teleop .claude/skills/run-teleop && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
run-teleop
GitHub stars
1.4k
Token cost
~915 tokens
SKILL.md length
262 words
Files
1
Skills in repo
26
Repo updated
First seen
Licence
MPL-2.0

At a glance

Launch the geniesimteleop VR / Pico teleoperation loop (or the in-process image bridge) using the geniesim teleop CLI verb, typically inside the Genie Sim GUI Docker container.

  • Works in 3 steps: Collect inputs → Launch the teleop loop → (optional) Image bridge
  • Asks to start teleop
  • SKILL.md covers When to Use, Critical Patterns, Workflow and Commands (copy-paste summary…, plus 1 more section
  • Calls python3

What it does

Run Teleop is an agent skill from AgibotTech/genie_sim. Launch the geniesimteleop VR / Pico teleoperation loop (or the in-process image bridge) using the geniesim teleop CLI verb, typically inside the Genie Sim GUI Docker container. Trigger: When the user asks to "start teleop", "run teleop", "启动遥操作", "VR 采集", "遥操作采集", "drive the robot with the VR headset", "launch the teleop loop", or wants to run anything under geniesimteleop.

Its SKILL.md is about 920 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud, covering Containers. It works with Docker. The repository describes itself as: Simulation Platform from AgiBot. The licence is MPL-2.0.

When your agent uses it

  • Asks to start teleop
  • Drive the robot with the VR headset
  • Launch the teleop loop
  • Wants to run anything under geniesimteleop

Example prompts

  • “start teleop”
  • “run teleop”
  • “drive the robot with the VR headset”
  • “/run-teleop”

Requirements

  • Python 3
  • Docker

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Collect inputs
  2. Launch the teleop loop
  3. (optional) Image bridge

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

Run Teleop loads about 915 tokens when it runs. Until then it costs about 98 tokens; SKILL.md has 262 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~98
When it runs · the whole SKILL.md, loaded when a task matches
~915

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

Auto-check passed

The automated check found no risky patterns in SKILL.md.

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). 262 words, ~915 tokens.

Download SKILL.mdSave it as .claude/skills/run-teleop/SKILL.md (or your agent's skills folder).
name
run-teleop
description
Launch the geniesim_teleop VR / Pico teleoperation loop (or the in-process image bridge) using the `geniesim teleop` CLI verb, typically inside the Genie Sim GUI Docker container. Trigger: When the user asks to "start teleop", "run teleop", "启动遥操作", "VR 采集", "遥操作采集", "drive the robot with the VR headset", "launch the teleop loop", or wants to run anything under `geniesim_teleop`.
license
MPL-2.0
metadata.author
genie-sim
metadata.version
1.0
prerequisites
geniesim_cli:fresh-machine-setup

When to Use

  • User wants to teleoperate the simulated robot with a VR device (Pico) and optionally record episodes.
  • User references geniesim_teleop, teleop.py, or the teleop bridge.

Do not use for:

  • Running a benchmark task → run-benchmark.
  • Verifying an inference server → check-inference.

Critical Patterns

  1. The runtime needs ROS 2 + Isaac Sim on the host. Inside the Genie Sim Docker image (geniesim docker up → geniesim docker into) that's already set up. Outside the container, source your ROS overlay and have Isaac Sim available.
  2. A VR device must be reachable. The teleop loop opens a VR server (default port 8080) and waits for the Pico headset to connect.
  3. Working directory: anywhere under the repo works — the CLI uses find_spec to locate the geniesim_teleop package.
  4. Confirm before launching. Teleop holds a GPU and a live device connection; ask before kicking it off if there's any ambiguity.

Workflow

Step 1 — Collect inputs

Ask via AskUserQuestion (all optional — sensible defaults exist):

  • Device type (default pico).
  • VR port (default 8080).
  • Robot config (default G2_omnipicker.json).
  • gRPC client host (default localhost:50051).
Step 2 — Launch the teleop loop

Inside the GUI container (geniesim docker into):

bash
geniesim teleop run --device_type=pico --port=8080

With explicit overrides:

bash
geniesim teleop run \
    --client_host=localhost:50051 \
    --port=8080 \
    --robot_cfg=G2_omnipicker.json \
    --device_type=pico
Step 3 — (optional) Image bridge

If the user needs the in-process image pub/sub bridge:

bash
geniesim teleop bridge --mode inprocess

Commands (copy-paste summary for the user)

bash
# Terminal A — host (start GUI container)
cd /path/to/main
./scripts/start_gui.sh

# Terminal B — host, then container
cd /path/to/main
./scripts/into.sh
# inside container:
geniesim teleop run --device_type=pico --port=8080

Notes

  • If geniesim isn't on $PATH, substitute python3 -m geniesim_cli teleop … — same args.
  • Any unknown --flag after the subcommand is forwarded verbatim to geniesim_teleop.teleop / geniesim_teleop.bridge.
  • Robot init states are loaded from the geniesim_benchmark package when it's installed; if it isn't, teleop still runs (init-state loading is skipped with a warning).

© 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_teleop/skills/run-teleop of AgibotTech/genie_sim.

Open the folder on GitHubat commit 6ca11c7

Compare with similar skills

Run Teleop next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Run Teleop compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Run Teleop this skillAgibotTech/genie_sim1.4k—~915Automated safety check: PassMPL-2.0
Iron Proxy Gateway for NanoClawnanocoai/nanoclaw31k—~4.6kAutomated safety check: NotesMIT
GreptimeDB Dev Docker ImageGreptimeTeam/greptimedb6.7k—~4kAutomated safety check: NotesApache-2.0
Senior DevOps Toolkitmaslennikov-ig/claude-code-orchestrator-kit2606 repos~1.1kAutomated safety check: NotesCustom licence
LangBot Deployment Guidelangbot-app/LangBot18k—~1.2kAutomated safety check: NotesApache-2.0
Build Openshell Mxc WindowsNVIDIA/OpenShell15k—~4.9kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Run Teleop

What does Run Teleop do?

Launch the geniesimteleop VR / Pico teleoperation loop (or the in-process image bridge) using the geniesim teleop CLI verb, typically inside the Genie Sim GUI Docker container. Run Teleop is an agent skill from AgibotTech/genie_sim. Launch the geniesimteleop VR / Pico teleoperation loop (or the in-process image bridge) using the geniesim teleop CLI verb, typically inside the Genie Sim GUI Docker container.

When should I use Run Teleop?

Run Teleop fits situations like: asks to start teleop; drive the robot with the VR headset; launch the teleop loop; wants to run anything under geniesimteleop.

How do I install Run Teleop in Claude Code?

Run `npx skills add AgibotTech/genie_sim --skill run-teleop -a claude-code`. Or copy the skill folder (source/geniesim_teleop/skills/run-teleop in AgibotTech/genie_sim) into .claude/skills/run-teleop in your project. Claude Code loads it when a task matches its description.

How do I install Run Teleop in Codex?

Run `npx skills add AgibotTech/genie_sim --skill run-teleop -a codex`. Or copy the skill folder (source/geniesim_teleop/skills/run-teleop in AgibotTech/genie_sim) into .agents/skills/run-teleop in your project. Codex loads it when a task matches its description.

Can I use Run Teleop in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add AgibotTech/genie_sim --skill run-teleop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/run-teleop, .gemini/skills/run-teleop, .github/skills/run-teleop and .opencode/skills/run-teleop in your project.

What does Run Teleop need to run?

Going by SKILL.md and its folder, Run Teleop needs the command-line tools its instructions call (python3). Our summary lists: Python 3; Docker.

Does Run Teleop access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Run Teleop safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Run Teleop use?

Run Teleop is published under the MPL-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Run Teleop use?

About 915 tokens (SKILL.md is roughly 3.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Run Teleop?

Skills that share tags, products or a category with Run Teleop: Iron Proxy Gateway for NanoClaw (nanocoai/nanoclaw, 31k stars), GreptimeDB Dev Docker Image (GreptimeTeam/greptimedb, 6.7k stars), Senior DevOps Toolkit (maslennikov-ig/claude-code-orchestrator-kit, 260 stars) and LangBot Deployment Guide (langbot-app/LangBot, 18k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Run Teleop?

AgibotTech (a GitHub organization) maintains it in AgibotTech/genie_sim, which has 1,414 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on September 7, 2026.

Source: AgibotTech/genie_sim on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.