Iron Proxy Gateway for NanoClaw
nanocoai/nanoclaw
Installs or refreshes Iron Proxy and its Iron Control web console for NanoClaw, with a local Docker setup, database, credentials and a human approval bridge.
Launch a geniesimbenchmark task locally (typically inside the GUI Docker container) against a user-provided inference server, using the geniesim benchmark run CLI verb.
Install Run Benchmark
$ npx skills add AgibotTech/genie_sim --skill run-benchmark -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install AgibotTech/genie_sim run-benchmark --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/AgibotTech/genie_sim.git skills-src && mkdir -p .claude/skills && cp -r skills-src/source/geniesim_benchmark/skills/run-benchmark .claude/skills/run-benchmark && rm -rf skills-srcUse ~/.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/
Install the "run-benchmark" agent skill from https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_benchmark/skills/run-benchmark into .claude/skills/run-benchmark/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-benchmark", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_benchmark/skills/run-benchmarkType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add AgibotTech/genie_sim --skill run-benchmark -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install AgibotTech/genie_sim run-benchmark --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AgibotTech/genie_sim.git skills-src && mkdir -p .agents/skills && cp -r skills-src/source/geniesim_benchmark/skills/run-benchmark .agents/skills/run-benchmark && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "run-benchmark" agent skill from https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_benchmark/skills/run-benchmark into .agents/skills/run-benchmark/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-benchmark", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add AgibotTech/genie_sim --skill run-benchmark -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install AgibotTech/genie_sim run-benchmark --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AgibotTech/genie_sim.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/source/geniesim_benchmark/skills/run-benchmark .cursor/skills/run-benchmark && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "run-benchmark" agent skill from https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_benchmark/skills/run-benchmark into .cursor/skills/run-benchmark/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-benchmark", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/AgibotTech/genie_sim.git --path source/geniesim_benchmark/skills/run-benchmark--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add AgibotTech/genie_sim --skill run-benchmark -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install AgibotTech/genie_sim run-benchmark --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AgibotTech/genie_sim.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/source/geniesim_benchmark/skills/run-benchmark .gemini/skills/run-benchmark && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "run-benchmark" agent skill from https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_benchmark/skills/run-benchmark into .gemini/skills/run-benchmark/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-benchmark", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install AgibotTech/genie_sim run-benchmarkInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add AgibotTech/genie_sim --skill run-benchmark -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/AgibotTech/genie_sim.git skills-src && mkdir -p .github/skills && cp -r skills-src/source/geniesim_benchmark/skills/run-benchmark .github/skills/run-benchmark && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "run-benchmark" agent skill from https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_benchmark/skills/run-benchmark into .github/skills/run-benchmark/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-benchmark", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add AgibotTech/genie_sim --skill run-benchmark -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install AgibotTech/genie_sim run-benchmark --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AgibotTech/genie_sim.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/source/geniesim_benchmark/skills/run-benchmark .opencode/skills/run-benchmark && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "run-benchmark" agent skill from https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_benchmark/skills/run-benchmark into .opencode/skills/run-benchmark/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-benchmark", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
run-benchmark- GitHub stars
- 1.4k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 381 words
- Files
- 1
- Skills in repo
- 26
- Repo updated
- First seen
- Licence
- MPL-2.0
At a glance
Launch a geniesimbenchmark task locally (typically inside the GUI Docker container) against a user-provided inference server, using the geniesim benchmark run CLI verb.
- Works in 4 steps: Collect inputs → Probe inference (optional but recommended) → Run the task → …
- Asks to run geniesim
- SKILL.md covers When to Use, Critical Patterns, Workflow and Commands (copy-paste summary…, plus 1 more section
- Calls python3
What it does
Run Benchmark is an agent skill from AgibotTech/genie_sim. Launch a geniesimbenchmark task locally (typically inside the GUI Docker container) against a user-provided inference server, using the geniesim benchmark run CLI verb. Trigger: When the user asks to "run geniesim", "本地跑仿真", "启动仿真任务", "run a benchmark", "launch <some<config.yaml", or wants to execute a benchmark task config (anything under geniesimbenchmark/config/.yaml) against a remote inference host (ip:port).
Its SKILL.md is about 1.3k 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 run geniesim
- Run a benchmark
- Launch <some<config.yaml
- Wants to execute a benchmark task config (anything under geniesimbenchmark/config/.yaml) against a remote inference host (ip:port)
Example prompts
- “run geniesim”
- “启动仿真任务”
- “run a benchmark”
- “/run-benchmark”
Requirements
- Python 3
- Docker
Workflow steps
4 steps, taken from the step headings in SKILL.md.
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 Benchmark loads about 1.3k tokens when it runs. Until then it costs about 110 tokens; SKILL.md has 381 words of instructions outside code blocks.
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). 381 words, ~1,307 tokens.
Download SKILL.mdSave it as
.claude/skills/run-benchmark/SKILL.md (or your agent's skills folder).- name
- run-benchmark
- description
- Launch a geniesim_benchmark task locally (typically inside the GUI Docker container) against a user-provided inference server, using the `geniesim benchmark run` CLI verb. Trigger: When the user asks to "run geniesim", "本地跑仿真", "启动仿真任务", "run a benchmark", "launch <some>_<config>.yaml", or wants to execute a benchmark task config (anything under `geniesim_benchmark/config/*.yaml`) against a remote inference host (ip:port).
- license
- MPL-2.0
- metadata.author
- genie-sim
- metadata.version
- 1.0
- prerequisites
- geniesim_cli:fresh-machine-setup
When to Use
- User wants to run a
geniesim_benchmarktask on their workstation (not the Challenge platform). - User has an inference server already running somewhere reachable and provides its
ip:port. - User references any task config under
source/geniesim_benchmark/src/geniesim_benchmark/config/.
Do not use for:
- Submitting jobs to the Challenge platform →
challenge-submit-job. - Verifying an inference server is healthy → use the
check-inferenceskill. - Adding a new benchmark task →
add-benchmark-task.
Critical Patterns
- Always collect three required inputs first:
- Task config (basename, full path, or substring — the CLI resolves all three).
- Inference IP.
- Inference port.
- The runtime needs
omni_python/ Isaac Sim on the host. Inside the Genie Sim Docker image (geniesim docker up→geniesim docker into), that's already the case. Outside the container the user needs Isaac Sim installed system-wide. - Working directory: anywhere under the repo root works — the CLI
walks up to find
scripts/and usesfind_specto locate the benchmark package. - Confirm before launching. The task spawns a full simulator and typically holds a GPU; ask before kicking it off if there's any ambiguity.
Workflow
Step 1 — Collect inputs
If the user hasn't named a config, list candidates:
geniesim benchmark categories # show category counts
geniesim benchmark robots # show robot counts
geniesim benchmark list --robot=<R> --category=<C>Then ask via AskUserQuestion:
- Task config: free-text (use the basename — e.g.
g2op_if_pick_block_color). - Inference host as
ip:port.
Step 2 — Probe inference (optional but recommended)
Before sinking minutes into Isaac Sim startup, sanity-check the server (uses the bundled corobot payload):
geniesim benchmark check-inference --infer-host=<IP>:<PORT>See the check-inference skill to override the payload.
Show full SKILL.md (148 more words)Show less
Step 3 — Run the task
Inside the GUI container (geniesim docker into):
geniesim benchmark run <CONFIG> --infer-host=<IP>:<PORT>Example:
geniesim benchmark run g2op_if_pick_block_color --infer-host=<IP>:<PORT>Step 4 — Pass-through overrides (when asked)
geniesim benchmark run forwards any unknown --key=value to the
benchmark's ParameterServer. Common ones:
| Flag | Meaning |
|---|---|
--app.headless=true | No GUI (required on remote / batch hosts) |
--benchmark.num_episode=N | Override episode count |
--benchmark.seed=N | RNG / instance-sampling seed |
--benchmark.record=true | Persist episode logs to output_dir |
--benchmark.policy_class=… | Use a different policy class |
Full schema: source/geniesim_benchmark/src/geniesim_benchmark/config/params.py.
Commands (copy-paste summary for the user)
# Host — start the container (GUI by default; add --headless on remote/batch hosts)
cd /path/to/main
geniesim docker up
# Host — drop into a shell inside the running container
geniesim docker into
# inside container:
geniesim status # verify the stack is healthy
geniesim benchmark check-inference --infer-host=<IP>:<PORT>
geniesim benchmark run <CONFIG> --infer-host=<IP>:<PORT>Notes
- If
geniesimisn't on$PATH(the launcher wasn't installed), substitutepython3 -m geniesim_cli benchmark …— same args, same behaviour. <CONFIG>accepts the bare basename (g2op_if_pick_block_color), a full path, or a unique substring.- For batch evaluations, prefer
geniesim benchmark batch --category=… --robot=…over a shell loop — it forwards extras consistently and prints a per-config pass/fail summary. - The new CLI replaces the older ad-hoc
omni_python app/app.py --config …invocation. The new form normalizes interpreter selection, host shorthand, and config resolution.
© 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/run-benchmark of AgibotTech/genie_sim.
Open the folder on GitHubat commit 6ca11c7
Compare with similar skills
Run Benchmark 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Run Benchmark this skillAgibotTech/genie_sim | 1.4k | — | ~1.3k | Automated safety check: Pass | MPL-2.0 | |
| Iron Proxy Gateway for NanoClawnanocoai/nanoclaw | 31k | — | ~4.6k | Automated safety check: Notes | MIT | |
| GreptimeDB Dev Docker ImageGreptimeTeam/greptimedb | 6.7k | — | ~4k | Automated safety check: Notes | Apache-2.0 | |
| Senior DevOps Toolkitmaslennikov-ig/claude-code-orchestrator-kit | 259 | 6 repos | ~1.1k | Automated safety check: Notes | Custom licence | |
| LangBot Deployment Guidelangbot-app/LangBot | 18k | — | ~1.2k | Automated safety check: Notes | Apache-2.0 | |
| Build Openshell Mxc WindowsNVIDIA/OpenShell | 15k | — | ~4.9k | Automated safety check: Pass | Apache-2.0 |
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Related
Works with
Categories
Questions about Run Benchmark
What does Run Benchmark do?
Launch a geniesimbenchmark task locally (typically inside the GUI Docker container) against a user-provided inference server, using the geniesim benchmark run CLI verb. Run Benchmark is an agent skill from AgibotTech/genie_sim. Launch a geniesimbenchmark task locally (typically inside the GUI Docker container) against a user-provided inference server, using the geniesim benchmark run CLI verb.
When should I use Run Benchmark?
Run Benchmark fits situations like: asks to run geniesim; run a benchmark; launch <some<config.yaml; wants to execute a benchmark task config (anything under geniesimbenchmark/config/.yaml) against a remote inference host (ip:port).
How do I install Run Benchmark in Claude Code?
Run `npx skills add AgibotTech/genie_sim --skill run-benchmark -a claude-code`. Or copy the skill folder (source/geniesim_benchmark/skills/run-benchmark in AgibotTech/genie_sim) into .claude/skills/run-benchmark in your project. Claude Code loads it when a task matches its description.
How do I install Run Benchmark in Codex?
Run `npx skills add AgibotTech/genie_sim --skill run-benchmark -a codex`. Or copy the skill folder (source/geniesim_benchmark/skills/run-benchmark in AgibotTech/genie_sim) into .agents/skills/run-benchmark in your project. Codex loads it when a task matches its description.
Can I use Run Benchmark 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-benchmark -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-benchmark, .gemini/skills/run-benchmark, .github/skills/run-benchmark and .opencode/skills/run-benchmark in your project.
What does Run Benchmark need to run?
Going by SKILL.md and its folder, Run Benchmark needs the command-line tools its instructions call (python3). Our summary lists: Python 3; Docker.
Does Run Benchmark 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 Benchmark 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 Benchmark use?
Run Benchmark 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 Benchmark use?
About 1.3k tokens (SKILL.md is roughly 5.2k 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 Benchmark?
Skills that share tags, products or a category with Run Benchmark: 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, 259 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 Benchmark?
AgibotTech (a GitHub organization) maintains it in AgibotTech/genie_sim, which has 1,413 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.