Agent skill

Challenge Help

by AgibotTech in AgibotTech/genie_sim

Entry point for the Simulation Challenge skill set. An agent skill from AgibotTech/genie_sim.

Custom licenceAuto-check: warningsBackend & APIs

Install Challenge Help

The automated check flagged lines worth reading first. See the safety section below.

skills CLI
$ npx skills add AgibotTech/genie_sim --skill challenge-help -a claude-code

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

GitHub CLI
$ gh skill install AgibotTech/genie_sim challenge-help --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_benchmark/skills/robocoliseum/challenge-help .claude/skills/challenge-help && 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
challenge-help
GitHub stars
1.4k
Token cost
~1.9k tokens
SKILL.md length
682 words
Files
1
Skills in repo
26
Repo updated
First seen
Licence
Custom licence

At a glance

Entry point for the Simulation Challenge skill set. An agent skill from AgibotTech/genie_sim.

  • Works in 10 steps: Always confirm before… → Read-only calls run without… → The gateway host is fixed at… → …
  • The user mentions the challenge
  • SKILL.md covers Stage map, Routing rules, Hard rules and Environment contract
  • Calls curl and pip; reaches robocoliseum.ai; needs CHALLENGE_TOKEN and JOB_TOKEN

What it does

Challenge Help is an agent skill from AgibotTech/genie_sim. Entry point for the Simulation Challenge skill set. Use when the user mentions the challenge, leaderboard, submitting a model, or any of the /api/challenge/ endpoints — this skill picks the right downstream skill for them.

Its SKILL.md is about 1.9k 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 Backend & APIs. The repository describes itself as: Simulation Platform from AgiBot.

When your agent uses it

  • The user mentions the challenge
  • Submitting a model
  • Any of the /api/challenge/ endpoints — this skill picks the right downstream skill for them

Example prompts

  • “/challenge-help”

Requirements

  • Python 3
  • A credential in CHALLENGE_TOKEN
  • A credential in JOB_TOKEN

Workflow steps

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

  1. Always confirm before challenge-submit-job (each submission consumes one daily submission slot) and before launching agent processes (they…
  2. Read-only calls run without confirmation: login, current-user-info, jobs/result/log, best-score, ranking, quota check.
  3. The gateway host is fixed at 120.92.88.78 and does not change. Defaults: BASE_URL=https://robocoliseum.ai (HTTP API base for all curl…
  4. board has a closed allowed-value set today. config.board accepts exactly one of instruction / spatial / manip / robust. Any other value…
  5. If CHALLENGE_TOKEN is missing or returns 401, jump to challenge-login first.
  6. Auto-pilot does not skip confirmation gates. If the user says "全程做完" / "do it end to end", you may merge the gates into a single up-front…
  7. 4xx is a semantic rejection, never a network blip. Do not retry a 400/401/403/404 just because the user says "可能是网络抖动" — only connection…
  8. Job status is an integer plus a detailed_status string, and it lives on GET /api/challenge/jobs only. /job/{id}/result returns {tasks…
  9. There is no official Simulation SDK package. The supported client is the inference repo's ./scripts/tunnel.sh; contestants writing their…
  10. Never quote the daily submission cap from memory. It's a platform setting, not a fixed contest constant, and it has changed. Read GET…

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:

    • curl
    • pip

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • robocoliseum.ai

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • CHALLENGE_TOKEN
    • JOB_TOKEN

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

Context cost

Challenge Help loads about 1.9k tokens when it runs. Until then it costs about 60 tokens; SKILL.md has 682 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~60
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

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: warnings

The automated check found patterns that need a careful read before installing.

  • WarningLinks to a raw public IP addressSKILL.md:64
    lenge/..."` calls) and `TUNNEL_ENDPOINT=ws://120.92.88.78/api/challenge/tunnel` (WebSocket tunnel for `tunnel.sh`/run-ag
  • WarningLinks to a raw public IP addressSKILL.md:87
    ob` (job response), else fixed default `ws://120.92.88.78/api/challenge/tunnel` | `challenge-run-agent` |

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

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 682 words (~1,859 tokens).

“You are an AI assistant helping a contestant operate the Simulation Challenge platform end to end. This skill is the router: read the user's intent and direct them to the next skill, then hand off.”

— opening of SKILL.md by AgibotTech, Custom licence
name
challenge-help

Read the full SKILL.md on GitHub

Files

Just SKILL.md in source/geniesim_benchmark/skills/robocoliseum/challenge-help of AgibotTech/genie_sim.

Open the folder on GitHubat commit 6ca11c7

Compare with similar skills

Challenge Help 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.

Challenge Help compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Challenge Help this skillAgibotTech/genie_sim1.4k—~1.9kAutomated safety check: WarnCustom licence
Configuring Horizoncoollabsio/coolify63k4 repos~898Automated safety check: PassMIT
Nestjs Best Practicesrolling-scopes/rsschool-app10k6 repos~1.2kAutomated safety check: PassMIT
Sub2API AdminWei-Shaw/sub2api43k1 repos~717Automated safety check: PassLGPL-3.0
Firecrawl Build Onboardingfirecrawl/firecrawl190k1 repos~1.4kAutomated safety check: NotesISC
Obsidian BasesAtmosphere/atmosphere3.8k22 repos~3.2kAutomated safety check: PassApache-2.0

Similar skills

  • Configuring Horizon

    coollabsio/coolify

    A skill your agent uses whenever the user mentions Horizon by name in a Laravel context.

    63k GitHub starsUsed in 4 repos~898 tokens
    Backend & APIsAuto-check passed
  • Nestjs Best Practices

    rolling-scopes/rsschool-app

    NestJS best practices and architecture patterns for building production-ready applications.

    10k GitHub starsUsed in 6 repos~1.2k tokens
    Backend & APIsAuto-check passed
  • Sub2API Admin

    Wei-Shaw/sub2api

    Manages a Sub2API deployment from the command line: accounts, redeem and invitation codes, groups, proxies, imports, exports and raw admin API calls.

    43k GitHub starsUsed in 1 repo~717 tokens
    Backend & APIsAuto-check passed
  • Firecrawl Build Onboarding

    firecrawl/firecrawl

    Gets Firecrawl working in a project: signs you in through the browser, saves FIRECRAWL_API_KEY to .env and picks the first SDK or REST path.

    190k GitHub starsUsed in 1 repo~1.4k tokens
    Backend & APIsAuto-check: notes
  • Obsidian Bases

    Atmosphere/atmosphere

    Create and edit Obsidian Bases (.base files) with views, filters, formulas, and summaries.

    3.8k GitHub starsUsed in 22 repos~3.2k tokens
    Backend & APIsAuto-check passed
  • Fortify Development

    coollabsio/coolify

    ACTIVATE when the user works on authentication in Laravel. An agent skill from coollabsio/coolify.

    63k GitHub starsUsed in 4 repos~1.9k tokens
    Backend & APIsAuto-check passed

More from AgibotTech/genie_sim

All 26 skills in this repo
  • Challenge Baseline Model

    AgibotTech/genie_sim

    Provision and launch the Simulation Challenge baseline inference model end to end: clone the inference code from a given git repo/branch, download the checkpoints from ModelScope into the repo's…

    1.4k GitHub stars~2.4k tokensUpdated 1 mo ago
    Auto-check passed
  • Challenge Download Datasets

    AgibotTech/genie_sim

    Download the Simulation Challenge LeRobot v2.1 training datasets from ModelScope using ./scripts/downloaddataset.sh.

    1.4k GitHub stars~960 tokensUpdated 1 mo ago
    Auto-check passed
  • Add Robot

    AgibotTech/genie_sim

    Bring a custom robot into the Genie Sim RT Engine — author / fix a xacro / URDF in geniesimrobotmodel, prep meshes with the offline tools (normalizeobjnames.py, diagnoseurdf.py, recomputeinertia.py…

    1.4k GitHub stars~2.1k tokensUpdated 1 mo ago
    Auto-check passed
  • Build Workspace

    AgibotTech/genie_sim

    Build the geniesimros colcon workspace inside the Genie Sim Docker container using the geniesim ros build CLI verb.

    1.4k GitHub stars~1.2k tokensUpdated 1 mo ago
    Auto-check passed
  • Challenge Inference Protocol

    AgibotTech/genie_sim

    Reference for the Simulation Challenge inference wire protocol — the exact obs (input) and action (output) message format exchanged between the gateway/genie-sim simulator and the contestant's…

    1.4k GitHub stars~1.7k tokensUpdated 1 mo ago
    Auto-check passed
  • Challenge Login

    AgibotTech/genie_sim

    A skill your agent uses when the contestant needs to obtain or refresh their Simulation Challenge JWT (CHALLENGETOKEN), or wants to inspect the current logged-in user.

    1.4k GitHub stars~1.6k tokensUpdated 1 mo ago
    Auto-check passed

Categories

Questions about Challenge Help

What does Challenge Help do?

Entry point for the Simulation Challenge skill set. An agent skill from AgibotTech/genie_sim. Challenge Help is an agent skill from AgibotTech/genie_sim. Entry point for the Simulation Challenge skill set.

When should I use Challenge Help?

Challenge Help fits situations like: the user mentions the challenge; submitting a model; any of the /api/challenge/ endpoints — this skill picks the right downstream skill for them.

How do I install Challenge Help in Claude Code?

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

How do I install Challenge Help in Codex?

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

Can I use Challenge Help 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 challenge-help -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/challenge-help, .gemini/skills/challenge-help, .github/skills/challenge-help and .opencode/skills/challenge-help in your project.

What does Challenge Help need to run?

Going by SKILL.md and its folder, Challenge Help needs the command-line tools its instructions call (curl and pip) and credentials named CHALLENGE_TOKEN and JOB_TOKEN. Our summary lists: Python 3; A credential in CHALLENGE_TOKEN; A credential in JOB_TOKEN.

Does Challenge Help access the network?

SKILL.md names 1 domain. In commands or code: robocoliseum.ai; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Challenge Help safe to install?

Our automated static check of SKILL.md flagged 2 warning(s): links to a raw public ip address. Read the flagged lines before installing; the check is not a guarantee either way.

What licence does Challenge Help use?

Challenge Help has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Challenge Help use?

About 1.9k tokens (SKILL.md is roughly 7.4k 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 Challenge Help?

Skills that share tags, products or a category with Challenge Help: Configuring Horizon (coollabsio/coolify, 63k stars), Nestjs Best Practices (rolling-scopes/rsschool-app, 10k stars), Sub2API Admin (Wei-Shaw/sub2api, 43k stars) and Firecrawl Build Onboarding (firecrawl/firecrawl, 190k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Challenge Help?

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.