Arcgis To Portaljs
datopian/portaljs
Migrate a whole ArcGIS Hub site into a PortalJS Arc portal end-to-end.
Deploy and run ML experiments on local, remote, Vast.ai, or Modal serverless GPU.
Install Run Experiment
$ npx skills add AI4Scientist/nano-scientist --skill run-experiment -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install AI4Scientist/nano-scientist run-experiment --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/AI4Scientist/nano-scientist.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/run-experiment .claude/skills/run-experiment && 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-experiment" agent skill from https://github.com/AI4Scientist/nano-scientist/tree/main/skills/run-experiment into .claude/skills/run-experiment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-experiment", 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/AI4Scientist/nano-scientist/tree/main/skills/run-experimentType 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 AI4Scientist/nano-scientist --skill run-experiment -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install AI4Scientist/nano-scientist run-experiment --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AI4Scientist/nano-scientist.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/run-experiment .agents/skills/run-experiment && 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-experiment" agent skill from https://github.com/AI4Scientist/nano-scientist/tree/main/skills/run-experiment into .agents/skills/run-experiment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-experiment", 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 AI4Scientist/nano-scientist --skill run-experiment -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install AI4Scientist/nano-scientist run-experiment --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AI4Scientist/nano-scientist.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/run-experiment .cursor/skills/run-experiment && 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-experiment" agent skill from https://github.com/AI4Scientist/nano-scientist/tree/main/skills/run-experiment into .cursor/skills/run-experiment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-experiment", 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/AI4Scientist/nano-scientist.git --path skills/run-experiment--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 AI4Scientist/nano-scientist --skill run-experiment -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install AI4Scientist/nano-scientist run-experiment --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AI4Scientist/nano-scientist.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/run-experiment .gemini/skills/run-experiment && 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-experiment" agent skill from https://github.com/AI4Scientist/nano-scientist/tree/main/skills/run-experiment into .gemini/skills/run-experiment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-experiment", 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 AI4Scientist/nano-scientist run-experimentInstalls 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 AI4Scientist/nano-scientist --skill run-experiment -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/AI4Scientist/nano-scientist.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/run-experiment .github/skills/run-experiment && 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-experiment" agent skill from https://github.com/AI4Scientist/nano-scientist/tree/main/skills/run-experiment into .github/skills/run-experiment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-experiment", 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 AI4Scientist/nano-scientist --skill run-experiment -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install AI4Scientist/nano-scientist run-experiment --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AI4Scientist/nano-scientist.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/run-experiment .opencode/skills/run-experiment && 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-experiment" agent skill from https://github.com/AI4Scientist/nano-scientist/tree/main/skills/run-experiment into .opencode/skills/run-experiment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-experiment", 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-experiment- GitHub stars
- 128
- Used in
- 4 other repos
- Token cost
- ~2.9k tokens
- SKILL.md length
- 977 words
- Files
- 1
- Skills in repo
- 74
- Repo updated
- First seen
- Licence
- None found
At a glance
Deploy and run ML experiments on local, remote, Vast.ai, or Modal serverless GPU.
- Works in 8 steps: Detect Environment → Pre-flight Check → Sync Code (Remote Only) → …
- User says run experiment
- SKILL.md covers Workflow, Key Rules and CLAUDE.md Example
- Calls ssh, python and git; reaches wandb.ai; needs WANDB_API_KEY
What it does
Run Experiment is an agent skill from AI4Scientist/nano-scientist. Deploy and run ML experiments on local, remote, Vast.ai, or Modal serverless GPU. Use when user says "run experiment", "deploy to server", "跑实验", or needs to launch training jobs.
Its SKILL.md is about 2.9k 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, covering Serverless. The repository describes itself as: An autonomous research agent that turns a topic into a peer-reviewed technical report.
When your agent uses it
- User says run experiment
- Deploy to server
- Needs to launch training jobs
Example prompts
- “run experiment”
- “deploy to server”
- “/run-experiment”
Requirements
- Python 3
- Docker
- A credential in WANDB_API_KEY
- A credential in YOUR_KEY
- Pre-approved tools (allowed-tools): Bash(*), Read, Grep, Glob, Edit, Write, Agent, Skill(serverless-modal)
Workflow steps
8 steps, taken from the step headings in SKILL.md.
- Detect Environment
- Pre-flight Check
- Sync Code (Remote Only)
- 5: W&B Integration (when wandb: true in CLAUDE.md)
- Deploy
- Verify Launch
- Feishu Notification (if configured)
- Auto-Destroy Vast.ai Instance (when gpu: vast and auto_destroy: true)
What it can do on your machine
Read from SKILL.md and the folder at commit 7132192. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
Bash(*)ReadGrepGlobEditWriteAgentSkill(serverless-modal)
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
sshpythongitmodalrsyncscpcondapip
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:
wandb.ai
Also links to:
cloud.vast.aimodal.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
WANDB_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Run Experiment loads about 2.9k tokens when it runs. Until then it costs about 49 tokens; SKILL.md has 977 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: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
allowed-tools: Bash(*), Read, Grep, Glob, Edit, Write, Agent, Skill(serverless-modal)
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
Without a licence we can't republish the file, so here is its outline and opening line. It has 977 words (~2,946 tokens).
“Deploy and run ML experiment: $ARGUMENTS”
- name
- run-experiment
- allowed-tools
- Bash(*), Read, Grep, Glob, Edit, Write, Agent, Skill(serverless-modal)
- argument-hint
- experiment-description
Files
Just SKILL.md in skills/run-experiment of AI4Scientist/nano-scientist.
Open the folder on GitHubat commit 7132192
Used in 4 other repositories
We found 9 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 4 other GitHub owners. This page covers the copy in AI4Scientist/nano-scientist, which our catalogue first saw on October 7, 2026.
- OpenLAIR/dr-clawskills/aris-run-experiment
- wanshuiyin/Auto-claude-code-research-in-sleepskills/run-experimentskills/skills-codex/run-experiment
- brycewang-stanford/Auto-Empirical-Research-Skillsskills/42-wanshuiyin-ARIS/skills/run-experimentskills/42-wanshuiyin-ARIS/skills/skills-codex/run-experiment
- Tai609/NebulaMatruntime/skills-bundle/aris-run-experimentruntime/aris/skills-nebulamat/aris-run-experiment+1 more
Compare with similar skills
Run Experiment 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 Experiment this skillAI4Scientist/nano-scientist | 128 | 4 repos | ~2.9k | Automated safety check: Notes | None | |
| Arcgis To Portaljsdatopian/portaljs | 2.4k | 1 repos | ~2k | Automated safety check: Pass | MIT | |
| AWS Serverless Edazxkane/aws-skills | 367 | 4 repos | ~3.2k | Automated safety check: Pass | MIT | |
| NubaseOtterMind/Nubase | 623 | — | ~2.2k | Automated safety check: Notes | Apache-2.0 | |
| Tianji Worker Operationsmsgbyte/tianji | 3.1k | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| AI Model NodejsTencentCloudBase/CloudBase-AI-Toolkit | 1.1k | 2 repos | ~5k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Run Experiment
What does Run Experiment do?
Deploy and run ML experiments on local, remote, Vast.ai, or Modal serverless GPU. Run Experiment is an agent skill from AI4Scientist/nano-scientist.ai, or Modal serverless GPU.
When should I use Run Experiment?
Run Experiment fits situations like: user says run experiment; deploy to server; needs to launch training jobs.
How do I install Run Experiment in Claude Code?
Run `npx skills add AI4Scientist/nano-scientist --skill run-experiment -a claude-code`. Or copy the skill folder (skills/run-experiment in AI4Scientist/nano-scientist) into .claude/skills/run-experiment in your project. Claude Code loads it when a task matches its description.
How do I install Run Experiment in Codex?
Run `npx skills add AI4Scientist/nano-scientist --skill run-experiment -a codex`. Or copy the skill folder (skills/run-experiment in AI4Scientist/nano-scientist) into .agents/skills/run-experiment in your project. Codex loads it when a task matches its description.
Can I use Run Experiment 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 AI4Scientist/nano-scientist --skill run-experiment -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-experiment, .gemini/skills/run-experiment, .github/skills/run-experiment and .opencode/skills/run-experiment in your project.
What does Run Experiment need to run?
Going by SKILL.md and its folder, Run Experiment needs the command-line tools its instructions call (ssh, python, git, modal, rsync and scp) and credentials named WANDB_API_KEY. Our summary lists: Python 3; Docker; A credential in WANDB_API_KEY; A credential in YOUR_KEY. Its frontmatter pre-approves these tools: Bash(*), Read, Grep, Glob, Edit, Write, Agent, Skill(serverless-modal).
Does Run Experiment access the network?
SKILL.md names 3 domains. In commands or code: wandb.ai; the agent is likely to contact it when it follows the instructions. As links in the text: cloud.vast.ai and modal.com. This is read from the text; nothing was executed.
Is Run Experiment safe to install?
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Run Experiment use?
No licence was found for Run Experiment or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Run Experiment use?
About 2.9k tokens (SKILL.md is roughly 12k 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 Experiment?
Skills that share tags, products or a category with Run Experiment: Arcgis To Portaljs (datopian/portaljs, 2.4k stars), AWS Serverless Eda (zxkane/aws-skills, 367 stars), Nubase (OtterMind/Nubase, 623 stars) and Tianji Worker Operations (msgbyte/tianji, 3.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Run Experiment?
AI4Scientist (a GitHub organization) maintains it in AI4Scientist/nano-scientist, which has 128 GitHub stars. The repository holds 74 skills in this directory. The repository was last updated on June 3, 2026.
Source: AI4Scientist/nano-scientist on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.