Recap
Soul-Brews-Studio/arra-oracle-skills-cli
Session orientation and awareness — retro summaries, handoffs, git state, focus.
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…
Install Challenge Baseline Model
$ npx skills add AgibotTech/genie_sim --skill challenge-baseline-model -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install AgibotTech/genie_sim challenge-baseline-model --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/robocoliseum/challenge-baseline-model .claude/skills/challenge-baseline-model && 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 "challenge-baseline-model" agent skill from https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_benchmark/skills/robocoliseum/challenge-baseline-model into .claude/skills/challenge-baseline-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "challenge-baseline-model", 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/robocoliseum/challenge-baseline-modelType 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 challenge-baseline-model -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install AgibotTech/genie_sim challenge-baseline-model --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/robocoliseum/challenge-baseline-model .agents/skills/challenge-baseline-model && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "challenge-baseline-model" agent skill from https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_benchmark/skills/robocoliseum/challenge-baseline-model into .agents/skills/challenge-baseline-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "challenge-baseline-model", 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 challenge-baseline-model -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install AgibotTech/genie_sim challenge-baseline-model --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/robocoliseum/challenge-baseline-model .cursor/skills/challenge-baseline-model && 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 "challenge-baseline-model" agent skill from https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_benchmark/skills/robocoliseum/challenge-baseline-model into .cursor/skills/challenge-baseline-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "challenge-baseline-model", 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/robocoliseum/challenge-baseline-model--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 challenge-baseline-model -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install AgibotTech/genie_sim challenge-baseline-model --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/robocoliseum/challenge-baseline-model .gemini/skills/challenge-baseline-model && 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 "challenge-baseline-model" agent skill from https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_benchmark/skills/robocoliseum/challenge-baseline-model into .gemini/skills/challenge-baseline-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "challenge-baseline-model", 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 challenge-baseline-modelInstalls 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 challenge-baseline-model -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/robocoliseum/challenge-baseline-model .github/skills/challenge-baseline-model && 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 "challenge-baseline-model" agent skill from https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_benchmark/skills/robocoliseum/challenge-baseline-model into .github/skills/challenge-baseline-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "challenge-baseline-model", 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 challenge-baseline-model -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 challenge-baseline-model --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/robocoliseum/challenge-baseline-model .opencode/skills/challenge-baseline-model && 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 "challenge-baseline-model" agent skill from https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_benchmark/skills/robocoliseum/challenge-baseline-model into .opencode/skills/challenge-baseline-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "challenge-baseline-model", 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
challenge-baseline-model- GitHub stars
- 1.4k
- Token cost
- ~2.4k tokens
- SKILL.md length
- 749 words
- Files
- 2 (incl. scripts)
- Skills in repo
- 26
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
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…
- Works in 4 steps: Clone the inference code → Download checkpoints (ModelScope) → Install dependencies → …
- Asks to 拉取 baseline 模型
- SKILL.md covers CONFIG — edit these (current =…, Step 1 — Clone the inference…, Step 2 — Download checkpoints… and Step 3 — Install dependencies, plus 2 more sections
- Runs Shell scripts from its folder; calls git, pip and uv; reaches github.com; needs CHALLENGE_TOKEN
What it does
Challenge Baseline Model is an agent skill from 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 local checkpoints path, install deps, and start the inference agent. Trigger: When the user asks to "拉取 baseline 模型", "下载推理代码/权重", "搭一个 baseline", "clone the inference repo", "download ckpts", "set up the baseline model", "跑起来 baseline", "provision the baseline", or hands over a repo URL to stand up an inference server…
Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/download_checkpoint.sh`).
It sits in Productivity & Automation, covering Meeting notes and agendas. It works with Git. The repository describes itself as: Simulation Platform from AgiBot.
When your agent uses it
- Asks to 拉取 baseline 模型
- Clone the inference repo
- Set up the baseline model
- Provision the baseline
Example prompts
- “拉取 baseline 模型”
- “下载推理代码/权重”
- “搭一个 baseline”
- “/challenge-baseline-model”
Requirements
- Python 3
- A Bash shell
- A credential in CHALLENGE_TOKEN
Workflow steps
4 steps, taken from the step headings in SKILL.md.
- Clone the inference code
- Download checkpoints (ModelScope)
- Install dependencies
- Run the inference agent
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
Ships 1 file in scripts/ (Shell), which the agent can run.
Shell commands in SKILL.md call:
gitpipuv
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:
github.com
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
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Challenge Baseline Model loads about 2.4k tokens when it runs. Until then it costs about 169 tokens; SKILL.md has 749 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); the scripts in this folder 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 749 words (~2,388 tokens).
“End-to-end setup of a contestant inference model: clone code → download checkpoints → install deps → run agent. Once running, the agent serves a Simulation Challenge job — hand off to challenge-run-agent for the launch contract and challenge-inference-protocol for the…”
- name
- challenge-baseline-model
- metadata.author
- zy
- metadata.version
- 1.0
Files
SKILL.md and 1 other file (scripts) in source/geniesim_benchmark/skills/robocoliseum/challenge-baseline-model of AgibotTech/genie_sim.
- SKILL.md
- scripts/download_checkpoint.sh
Open the folder on GitHubat commit 6ca11c7
Compare with similar skills
Challenge Baseline Model 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 |
|---|---|---|---|---|---|---|
| Challenge Baseline Model this skillAgibotTech/genie_sim | 1.4k | — | ~2.4k | Automated safety check: Pass | Custom licence | |
| RecapSoul-Brews-Studio/arra-oracle-skills-cli | 122 | — | ~2.7k | Automated safety check: Pass | MIT | |
| Team Updatejezweb/claude-skills | 1.1k | — | ~2.3k | Automated safety check: Pass | MIT | |
| Deadline Prepdavila7/claude-code-templates | 32k | — | ~739 | Automated safety check: Pass | MIT | |
| Lark Todoautumnseasonism/lark-todo | 138 | — | ~5.5k | Automated safety check: Pass | MIT | |
| Claap Weekly RecapOthmane-Khadri/YALC-the-GTM-operating-system | 317 | — | ~5.4k | Automated safety check: Pass | MIT |
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jezweb/claude-skills
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Lark Todo
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飞书全平台待办扫描：IM 消息、会议纪要、日程、文档评论、待办审批、我发起的审批、邮件、已有任务八源并行采集，按优先级排序后支持直接处理或建任务。多企业账号自动发现并并行扫描，跨企业合并。用户说'有啥待办'、'@我的消息'、'扫一圈'、'收工检查'、'今天还差啥'、'morning standup'、'daily review' 时触发，连随口'忙不忙'、'有人找我吗'也应触发。同时覆盖多企业…
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Related
Works with
Categories
Questions about Challenge Baseline Model
What does Challenge Baseline Model do?
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…. Challenge Baseline Model is an agent skill from 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 local checkpoints path, install deps, and start the inference agent.
When should I use Challenge Baseline Model?
Challenge Baseline Model fits situations like: asks to 拉取 baseline 模型; clone the inference repo; set up the baseline model; provision the baseline.
How do I install Challenge Baseline Model in Claude Code?
Run `npx skills add AgibotTech/genie_sim --skill challenge-baseline-model -a claude-code`. Or copy the skill folder (source/geniesim_benchmark/skills/robocoliseum/challenge-baseline-model in AgibotTech/genie_sim) into .claude/skills/challenge-baseline-model in your project. Claude Code loads it when a task matches its description.
How do I install Challenge Baseline Model in Codex?
Run `npx skills add AgibotTech/genie_sim --skill challenge-baseline-model -a codex`. Or copy the skill folder (source/geniesim_benchmark/skills/robocoliseum/challenge-baseline-model in AgibotTech/genie_sim) into .agents/skills/challenge-baseline-model in your project. Codex loads it when a task matches its description.
Can I use Challenge Baseline Model 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-baseline-model -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-baseline-model, .gemini/skills/challenge-baseline-model, .github/skills/challenge-baseline-model and .opencode/skills/challenge-baseline-model in your project.
What does Challenge Baseline Model need to run?
Going by SKILL.md and its folder, Challenge Baseline Model needs a shell for the scripts in its folder, the command-line tools its instructions call (git, pip and uv) and credentials named CHALLENGE_TOKEN. Our summary lists: Python 3; A Bash shell; A credential in CHALLENGE_TOKEN.
Does Challenge Baseline Model access the network?
SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Is Challenge Baseline Model 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Challenge Baseline Model use?
Challenge Baseline Model 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 Baseline Model use?
About 2.4k tokens (SKILL.md is roughly 9.6k 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 Baseline Model?
Skills that share tags, products or a category with Challenge Baseline Model: Recap (Soul-Brews-Studio/arra-oracle-skills-cli, 122 stars), Team Update (jezweb/claude-skills, 1.1k stars), Deadline Prep (davila7/claude-code-templates, 32k stars) and Lark Todo (autumnseasonism/lark-todo, 138 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Challenge Baseline Model?
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.