Experiment Bridge
Turns an experiment plan into running GPU experiments with initial results.
- Stars
- 18,482
- Licence
- MIT
- Files
- 1 file
What it does
When installed, the agent reads an experiment plan (EXPERIMENT_PLAN.md) produced by an earlier research step, writes the experiment code (training, evaluation, baselines, seeds, JSON/CSV results), optionally asks a second AI model to review that code for bugs, then deploys the runs to a GPU and collects the first results. It is the bridge between choosing a research idea and running the automated review loop.
Great for
- Researchers who already have a written experiment plan and want the code implemented and launched
- ML students running sanity, baseline and ablation experiments on a GPU
Skip it if
- People without an experiment plan or GPU access: the skill assumes the earlier planning workflow exists and deploys real compute jobs
- Production or sensitive environments: it runs arbitrary Bash commands, may clone repos and call external AI reviewer services, so review its actions before letting it deploy
Try asking
- “Implement the experiments in refine-logs/EXPERIMENT_PLAN.md and deploy the sanity run first”
- “Bridge my idea into experiments: implement experiments from the plan and collect initial results”
- “Clone https://github.com/org/project as the base repo and implement the planned ablations on top of it”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 1 original files, the MIT licence and an attribution note.
experiment-bridge.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip experiment-bridge.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip experiment-bridge.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 3
Ask for the task
No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.
Get better results
- Run the sanity experiment first and read its output before allowing the full batch to launch
- Keep CODE_REVIEW enabled and set AUTO_DEPLOY to false if you want to inspect generated code before GPU time is spent
- Check the research contract and plan paths exist before starting so the skill does not have to guess
What's inside
- SKILL.md
Redistributed unmodified from wanshuiyin/Auto-claude-code-research-in-sleep under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.