Individual skill
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.
skills/skills-codex/experiment-bridge/SKILL.md
Source commit 2901234ad2954cd2388ced8d3aed2ed9de42803a
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- Observed behavior
- Network or broad shell
- Last checked
- Nov 9, 2026
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Repository context
- Repository stars (not skill ratings)
- 18,965
- Repository last updated
- Nov 8, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai-research Repository topic
- autonomous-agent Repository topic
- claude-code Repository topic
- codex Repository topic
- mcp Repository topic
- ml-research Repository topic
- paper-review Repository topic
- research-automation Repository topic
- ai-tools Repository topic
- claude Repository topic
- operations Derived category
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# Workflow 1.5: Experiment Bridge
> **Before each reviewer slot**, follow [Selectable Reviewers](../shared-references/reviewer-backends.md):
> resolve invocation → `.aris/reviewer.json` → Codex default (fresh native reviewer)
> 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**