AutoSci is an AI research platform organized around a wiki, with an agent that supports stages of scientific work such as reading, experimentation, writing, and retaining knowledge across projects. It is for people building or using AI-assisted research workflows, with Claude Code, Codex, and OpenCode adaptations available. The catalogue add-ons extend those agent-specific workflows.
Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
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.
[](https://agentmods.dev/skills/skyllwt/autosci/exp-run)<a href="https://agentmods.dev/skills/skyllwt/autosci/exp-run"><img src="https://agentmods.dev/badge/skills/skyllwt/autosci/exp-run.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 5.1 | $0.00035 | $0.04807 |
| Opus 5 | $0.00017 | $0.02403 |
| Sonnet 5 | $0.00007 | $0.00961 |
| Haiku 4.5 | $0.00003 | $0.00481 |
Grade A, and why
exp-run 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.
How it starts
The opening of the file, as written. The whole thing — 419 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/exp-run
Execute an experiment that has been planned in wiki/experiments/. No matter which operation mode it is, before preparing the experimental codes and deploying them for operation, confirmation shall be obtained from users. Users need to manually check relevant information such as codes and experimental configurations(Dataset paths, interface parameter selection, API configuration, etc.). The operation can only be launched after confirmation; otherwise, revisions shall be made repeatedly until users approve the execution. Three run modes for different scenarios:
- Default (deploy): Phase 1-2 only — deploy and return immediately. Best for experiments that take hours or days.
--collect: Phase 3-4 only — check whether a deployed experiment has finished; collect results if so (--checkis an alias).--full: All four phases end-to-end. Best for short local experiments that finish in minutes.Recommended flow:
/exp-run <slug>to deploy →/exp-statusto monitor →/exp-run <slug> --collectto collect.
Inputs
experiment: slug from wiki/experiments/- deploy mode: status must be
planned - --collect mode: status must be
running - --full mode: status must be
planned
- deploy mode: status must be
--review(optional): enable Review LLM code review for experiment code in Phase 1 (valid in deploy / full mode)--collect(optional): collect mode — check if the experiment has finished and collect results;--checkis an alias--full(optional): full mode — execute all 4 phases (best for quick local experiments)--env local|remote(optional, defaultlocal): deployment environmentlocal: run directly on local GPUremote: deploy to remote machine via SSH (requiresconfig/server.yaml)
Outputs
- deploy mode:
- Experiment code:
experiments/code/{slug}/(generated in Phase 1) wiki/experiments/{slug}.md— status: planned → running- DEPLOY_REPORT (printed to terminal) — deployment confirmation, session info, next steps
wiki/log.md— appended deploy log
- Experiment code:
- collect mode (experiment has finished):
wiki/experiments/{slug}.md— status: running → completed; outcome/key_result/date_completed filled in- RUN_REPORT (printed to terminal) — result summary, metrics comparison, next step suggestions
wiki/log.md— appended collect log
- collect mode (experiment still running):
- Progress report printed to terminal only; wiki is not modified
- full mode: all outputs from both deploy and collect
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.
- 6d ago First seen · 419 lines · 35 tokens per session scan A 528b94ed5496
exp-run is a skill published in the GitHub repository skyllwt/AutoSci (1,660 stars, last pushed today), licensed MIT. It adds 35 tokens to every session and 4,807 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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