Experiment Bridge
Workflow 1.5: Bridge between idea discovery and auto review.
Install
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill experiment-bridge -g -a claude-code -y- Repository
- wanshuiyin/Auto-claude-code-research-in-sleep18.4k
- Category
- DevOps
- Updated
- 4d ago
- License
- MIT
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- No, instructions only
What it does
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.
Workflow 1.5: Experiment Bridge
Before each reviewer slot, follow Selectable Reviewers: resolve invocation →
.aris/reviewer.json→ Claude Code default (Codex MCP) withreviewer_route.pythrough the canonical helper resolver, preserving this slot's tier, fresh contexts, source/image inputs and deterministic gates. Codex examples/pins below apply only tobackend=codex; other routes use their own first-call/reply contract. Save the route and actual returned identity; unavailable selections areREVIEW_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
