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experiment-bridge

experiment-bridge is a skill for Claude Code from raja21068/AutoResearch. It costs 74 tokens per session (3,714 once invoked), scanned A, a copy of experiment-bridge, MIT.

A workflow tool that turns a research experiment plan into implemented code, deployed runs on GPUs, and initial results. It connects planning, code review, execution, and result collection.

In plain words
What is it for?
Use it when an experiment plan is ready and you need to implement it, review the code, deploy runs, and collect results for later evaluation.
Why use it?
It reduces the gap between deciding what to test and actually running it, while checking the experiment code and starting with a small sanity test.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions CLAUDE.md; mentions Codex.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is - **[Output Versioning Protocol](../shared-references/output-versioning.md)** — write timestamped file first, then copy to fixed name.

not rated 2repo 3mo ago A scan 74 tokens copy · 95% MIT

Good fit Use it when an experiment plan is ready and you need to implement it, review the code, deploy runs, and collect results for later evaluation.

Compare 6 skills from other repositories ↓
View source ↗ raja21068/AutoResearch
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/raja21068/AutoResearch
agentmods
npx agentmods add skills/raja21068/autoresearch/experiment-bridge

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for experiment-bridge

README.md
[![agentmods](https://agentmods.dev/badge/skills/raja21068/autoresearch/experiment-bridge/github.svg)](https://agentmods.dev/skills/raja21068/autoresearch/experiment-bridge)
Your own site
<a href="https://agentmods.dev/skills/raja21068/autoresearch/experiment-bridge"><img src="https://agentmods.dev/badge/skills/raja21068/autoresearch/experiment-bridge/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for experiment-bridge

Your own site · 80×15
<a href="https://agentmods.dev/skills/raja21068/autoresearch/experiment-bridge"><img src="https://agentmods.dev/badge/skills/raja21068/autoresearch/experiment-bridge.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,714 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 95% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00074 $0.03714
Opus 5 $0.00037 $0.01857
Sonnet 5 $0.00015 $0.00743
Haiku 4.5 $0.00007 $0.00371

Measured 6d ago against content hash 219f1d5ee000, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

experiment-bridge scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

95% identical to experiment-bridge — 63 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/aris/experiment-bridge/SKILL.md · 330 lines

How it starts

The opening of the file, as written. The whole thing — 330 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 → GPT-5.4 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

  • CODE_REVIEW = true — GPT-5.4 xhigh reviews experiment code before deployment. Catches logic bugs before wasting GPU hours. Set false to skip.
  • AUTO_DEPLOY = true — Automatically deploy experiments after implementation + review. Set false to manually inspect code before deploying.
  • 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 base codebase. When set, clone the repo first and implement experiments on top of it. When false (default), write code from scratch or reuse existing project files.
  • COMPACT = false — When true, (1) read idea-stage/IDEA_CANDIDATES.md instead of full idea-stage/IDEA_REPORT.md if available, (2) append experiment results to EXPERIMENT_LOG.md after collection.

Override: /experiment-bridge "EXPERIMENT_PLAN.md" — compact: true, base repo: https://github.com/org/project

Inputs

This skill expects one or more of:

  1. refine-logs/EXPERIMENT_PLAN.md (best) — claim-driven experiment roadmap from /experiment-plan
  2. refine-logs/EXPERIMENT_TRACKER.md — run-by-run execution table
  3. refine-logs/FINAL_PROPOSAL.md — method description for implementation context
  4. idea-stage/IDEA_CANDIDATES.md — compact idea summary (preferred when COMPACT: true) (fall back to ./IDEA_CANDIDATES.md if not found)
  5. idea-stage/IDEA_REPORT.md — full brainstorm output (fall back to ./IDEA_REPORT.md if not found)

Read the full file on GitHub · 330 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 330 lines · 74 tokens per session scan A 219f1d5ee000

Subscribe to this mod's changes

experiment-bridge is a skill published in the GitHub repository raja21068/AutoResearch (2 stars, last pushed 3mo ago), licensed MIT. It adds 74 tokens to every session and 3,714 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to experiment-bridge, differing in 63 lines, and is treated as a copy.

Claude CodeData and AIScientificagentic-aianthropicantigravityarvixautomated-paper-writing
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