Challenge Ranking logo

Challenge Ranking

OrganizationPopular
AgibotTech
challenge-ranking

Use to fetch the contestant's best score and the per-board leaderboard for the Simulation Challenge. Read-only; safe to run without confirmation.

Overview

PublisherAgibotTech
Repositorygenie_sim
Skill namechallenge-ranking
Stars
1.4K
Forks
119
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by AgibotTech on GitHub. Read the source before you install it.

Installation

Install the Challenge Ranking AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AgibotTech/genie_sim.git /tmp/genie_sim
mkdir -p .claude/skills
cp -r /tmp/genie_sim/source/geniesim_benchmark/skills/robocoliseum/challenge-ranking .claude/skills/challenge-ranking
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Challenge Ranking in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Challenge Ranking on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Challenge Ranking is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

challenge-ranking — Best score and leaderboard

All endpoints here are read-only.

Board scoping. Best-score, rank, and leaderboard are all per-board: there is no global "total" score, and the same user can have four independent best-score / rank tuples (one per board: instruction / spatial / manip / robust). Always ask the user which board they care about, or report all four — never silently average.

Preconditions

  • CHALLENGE_TOKEN set for best-score (else → challenge-login).
  • The leaderboard endpoints (/leaderboard, /leaderboard/top5, /leaderboard/citation) are public — they work without a token, but include Authorization when you have one to stay symmetric with the rest of the skill set.

Every Bash call should start with:

bash
[ -f ~/.simubotix-challenge.env ] && . ~/.simubotix-challenge.env

My best score and rank (per board)

best-score requires a board query parameter (it filters the user's per-board best):

bash
[ -f ~/.simubotix-challenge.env ] && . ~/.simubotix-challenge.env
curl -fsS "$BASE_URL/api/challenge/best-score?board=instruction" \
  -H "Authorization: Bearer $CHALLENGE_TOKEN" | jq
# { "status": "ok", "score": 573.0, "rank": 5 }

Replace instruction with spatial / manip / robust as needed. Report score and rank plainly. If status is "error" (or rank is 0), the user has no scored submission on that board yet — suggest they run challenge-submit-job against it.

To get a quick all-board summary, fan out in parallel:

bash
for b in instruction spatial manip robust; do
  printf '%-12s ' "$b"
  curl -fsS "$BASE_URL/api/challenge/best-score?board=$b" \
    -H "Authorization: Bearer $CHALLENGE_TOKEN" | jq -c '{score, rank}'
done

Per-board leaderboard

bash
curl -fsS "$BASE_URL/api/challenge/leaderboard?board=instruction&page=1&per-page=20" \
  -H "Authorization: Bearer $CHALLENGE_TOKEN" | jq

Query param is per-page with a hyphen (per_page is silently ignored and you get the default 20). The response envelope echoes it back as per_page — same asymmetry as /api/challenge/jobs.

Each row is one user's best job for that board. Optional query params: sort (default score), order (asc / desc, default desc), q (substring search over user / organization name).

There is no rank_change field — only the current rank/score. Do not invent deltas.

Top-5 hero (all boards at once)

For a homepage-style overview without four separate calls:

bash
curl -fsS "$BASE_URL/api/challenge/leaderboard/top5" | jq
# { "boards": { "instruction": [...top 5], "spatial": [...], "manip": [...], "robust": [...] } }

Public, no auth needed.

Per-board detail (one user's per-task breakdown)

bash
curl -fsS "$BASE_URL/api/challenge/leaderboard/instruction/detail?user_uid=<uid>" | jq

The {board} path segment must be one of instruction / spatial / manip / robust. user_uid is the target user's UID (find it via the leaderboard row).

Citation (BibTeX)

bash
curl -fsS "$BASE_URL/api/challenge/leaderboard/citation" | jq -r '.citation // .'

Returns the platform-configured BibTeX string verbatim — surface as-is.

Pagination

If the user wants their own row and they're past page 1, walk pages until you hit their name. Keep per-page ≤ 100 to stay polite.

Hand-off

  • User wants to improve their rank on a specific board → challenge-submit-job (mind the daily submission quota — check /api/challenge/submission/quota; each board needs its own submission).
  • User wants their score for a specific recent submission → challenge-poll-result.

Frequently asked questions

What does the Challenge Ranking AI skill do?

Use to fetch the contestant's best score and the per-board leaderboard for the Simulation Challenge. Read-only; safe to run without confirmation.

Why use Challenge Ranking on TypingMind?

Because you install it once and use it with any model. Challenge Ranking is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Challenge Ranking in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_benchmark/skills/robocoliseum/challenge-ranking. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Challenge Ranking?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Challenge Ranking?

As many as you like. As long as a model supports skills, you can use Challenge Ranking with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Challenge Ranking AI skill free?

It is published on GitHub by AgibotTech. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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