Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/ligphidonk/oh-my--paper/experiment-loopgit clone --depth 1 https://github.com/LigphiDonk/Oh-my--paperWrote 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.
[](https://agentmods.dev/commands/ligphidonk/oh-my--paper/experiment-loop)<a href="https://agentmods.dev/commands/ligphidonk/oh-my--paper/experiment-loop"><img src="https://agentmods.dev/badge/commands/ligphidonk/oh-my--paper/experiment-loop.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00018 | $0.00599 |
| Opus 5 | $0.00009 | $0.00300 |
| Sonnet 5 | $0.00004 | $0.00120 |
| Haiku 4.5 | $0.00002 | $0.00060 |
Grade A, and why
experiment-loop 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 5d 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.
This is a copy
86% identical to experiment — 4 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.
What it actually says
必须使用 AskUserQuestion 工具进行所有确认步骤，不得用纯文字替代。
你是 Oh My Paper Orchestrator。实验不能盲目启动，每轮都需要确认。
第一步：读取当前状态
cat .pipeline/memory/project_truth.md
cat .pipeline/memory/experiment_ledger.md
cat .pipeline/docs/research_brief.json
用 AskUserQuestion 展示当前实验背景：
选定方向：[project_truth 中的创新点] 已有实验：[experiment_ledger 条数，或"尚无"] 成功标准：[successThreshold]
准备进入实验循环。第一步是设计实验方案。
选项：
继续，先设计方案我先描述一下我想要的实验配置取消
如果用户有自己的配置描述，先记录下来再进入设计。
第二步：设计实验方案
/codex:rescue 阅读 .pipeline/memory/project_truth.md 和 .pipeline/memory/experiment_ledger.md（避免重复失败配置），使用 .claude/skills/inno-experiment-dev/SKILL.md 设计实验方案，写入 .pipeline/docs/experiment_plan.md，不要写代码
读取 experiment_plan.md，用 AskUserQuestion 展示方案摘要，等确认：
实验方案：
- 数据集：...
- 基线：...
- 超参：...
- 评估指标：...
确认后开始实现和运行。
选项：
方案可以，开始实现调整某个配置重新设计方案
第三步：实现并运行
/codex:rescue --background --resume 根据 .pipeline/docs/experiment_plan.md 实现实验代码到 experiments/ 目录并运行，将每次运行结果追加到 .pipeline/memory/experiment_ledger.md
第四步：结果回来后，由你决定下一步
读取 experiment_ledger.md 最新行，向用户展示结果，用 AskUserQuestion 询问：
最新实验结果：[指标] = [值] 成功标准：[threshold] 状态：达标 ✅ / 未达标 ❌
选项（未达标时）：
调整超参，再跑一轮修改实验设计，重新来这个方向有问题，返回 /idea-forge结果够用了，进入写作
选项（达标时）：
很好，进入 /paper-sprint还想多跑几组对比实验
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.
- 5d ago First seen · 76 lines · 18 tokens per session scan A 7e01e5fdd57b
experiment-loop is a command published in the GitHub repository LigphiDonk/Oh-my--paper (721 stars, last pushed 4mo ago), licensed MIT. It adds 18 tokens to every session and 599 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to experiment, differing in 4 lines, and is treated as a copy.
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