experiment-bridge
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.
npx skills add majiayu000/claude-skill-registry --skill experiment-bridge-wanshuiyin-auto-claude-code-res --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Workflow 1.5: Experiment Bridge 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 → deploy → collect → initial results ready refine-logs/EXPERIMENT_TRACKER.md code /run-experiment for /auto-review-loop refine-logs/FINAL_PROPOSAL.md ``` ## Constants - **AUTO_DEPLOY = true** — Automatically deploy experiments after implementation. Set `false` to review code before deploying. - **CODE_REVIEW = true** — Secondary Codex reviewer with xhigh reasoning reviews experiment code before deployment. Catches logic bugs before wasting GPU hours. Set `false` to skip. - **SANITY_FIRST = true** — Run the sanity-stage experiment first (smallest, fastest) before launching the rest. Catches setup bugs early. - **MAX_PARALLEL_RUNS = 4** — Maximum number of experiments to deploy in parallel (limited by available GPUs). - **BASE_REPO = false** — GitHub repo URL to use as a base codebase. When set, clo
- Overview
- Constants
- Inputs
- Workflow
- Phase 1: Parse the Experiment Plan
- Phase 2: Implement Experiment Code
- Phase 2.5: Cross-Model Code Review (when CODEREVIEW = true)
- Phase 3: Sanity Check (if SANITYFIRST = true)
- Phase 4: Deploy Full Experiments
- Phase 5: Collect Initial Results
- Phase 5.5: Write Compact Log (when COMPACT = true)
- Phase 5.6: Auto Ablation Planning
- Phase 6: Handoff
- Output Protocols
git clone <BASE_REPO> base_repo/
What does the experiment-bridge skill do?
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.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill experiment-bridge-wanshuiyin-auto-claude-code-res --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.