# Experiment Bridge

Workflow 1.5: Bridge between idea discovery and auto review.

- Repository: https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep (18443 stars)
- Category: DevOps
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill experiment-bridge -g -a claude-code -y`
Codex: `npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill experiment-bridge -g -a codex -y`
Cursor: `npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill experiment-bridge -g -a cursor -y`
Gemini CLI: `npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill experiment-bridge -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add wanshuiyin/Auto-claude-code-research-in-sleep`

## Description

Workflow 1.5: Bridge between idea discovery and auto review. Reads EXPERIMENT_PLAN.md, implements experiment code, deploys to GPU, collects initial results. Use when user says \"实现实验\", \"implement experiments\", \"bridge\", \"从计划到跑实验\", \"deploy the plan\", or has an experiment plan ready to execute.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Workflow 1.5: Experiment Bridge

> **Before each reviewer slot**, follow [Selectable Reviewers](../shared-references/reviewer-backends.md):
> resolve invocation → `.aris/reviewer.json` → Claude Code default (Codex MCP)
> with `reviewer_route.py` through the canonical helper resolver, preserving this
> slot's tier, fresh contexts, source/image inputs and deterministic gates.
> Codex examples/pins below apply only to `backend=codex`; other routes use their
> own first-call/reply contract. Save the route and actual returned identity;
> unavailable selections are `REVIEW_UNAVAILABLE`. Classify acceptance from actual
> families/completion/scope. Forward invocation reviewer/model/effort overrides
> to reviewer-bearing children. Generation workers are unchanged.


Implement and deploy experiments from plan: **$ARGUMENTS**

## Overview

This skill bridges Workflow 1 (idea discovery + method refinement) and Workflow 2 (auto review loop). It takes the experiment plan and turns it into running experiments with initial results.

```
Workflow 1 output:                    This skill:                                    Workflow 2 input:
refine-logs/EXPERIMENT_PLAN.md   →   implement → GPT-6-Astra review → deploy → collect → initial results ready
refine-logs/EXPERIMENT_TRACKER.md     code        (cross-model)    /run-experiment     for /auto-review-loop
refine-logs/FINAL_PROPOSAL.md
```

## Constants

The rest: https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/blob/HEAD/skills/experiment-bridge/SKILL.md