synthetic-sciences/openscience is an AI workbench that carries out scientific research by reading papers, forming hypotheses, writing and running code, conducting experiments, analyzing results, and preparing reports. Researchers use it for work in machine learning, biology, physics, and chemistry with remote or local models. Catalogue add-ons extend its scientific workflows through skills and instructions.
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 skills add synthetic-sciences/openscience --skill runpodgit clone --depth 1 https://github.com/synthetic-sciences/openscienceWrote 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/synthetic-sciences/openscience/runpod)<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/runpod"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/runpod/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.
<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/runpod"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/runpod.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00032 | $0.00750 |
| Opus 5.5 | $0.00013 | $0.00300 |
| Sonnet 5.5 | $0.00006 | $0.00150 |
| Haiku 4.5 | $0.00003 | $0.00075 |
Grade A, and why
runpod-gpu-cloud 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 1mo 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RunPod GPU Cloud
Use this skill for RunPod identity, Pod, and related compute workflows. RunPod product surfaces and CLI commands evolve; distinguish Pods from Serverless and verify the current command reference for the requested product.
OpenScience credential boundary
- A key saved in Customize > Compute > RunPod is encrypted control-plane data and is not exported to Bash, Task, notebooks, kernels, plugins, or MCP servers.
- Use
provider_computewithaccount,list_resources,resource_status, orlist_availabilityfor live account, Pod, Pod-detail, and GPU availability reads. OpenScience owns the exact reviewedrunpodctlargv. - Test connection uses the same boundary for exactly
runpodctl user. - The saved key is admitted only when Test connection approves a root/admin-managed, non-writable
runpodctlexecutable. A normal user-owned Homebrew or manual install remains credential-only and cannot be used byprovider_computeuntil a managed/native adapter exists. - OpenScience updates
last_usedonly after the command succeeds. - Never print or persist the key. The saved credential cannot create, start, stop, restart, update, delete, transfer, or change resources; dashboard storage does not authenticate a generic agent shell.
Current CLI contract
runpodctl --help
runpodctl user
Use the installed runpodctl help and current official docs to select the current read-only list/status command, then again before constructing any mutation. Do not reuse remembered Pod create, Serverless, registry, or storage flags.
Operating policy
- Confirm the product surface, GPU memory/count, cloud type or reliability needs, region, image, disk/volume, ports, runtime estimate, interruption tolerance, and maximum budget.
- Query current inventory and provider-displayed pricing immediately before a recommendation.
- Present one recommended configuration and the exact live quoted terms. Label total cost as an estimate.
- Get explicit approval before creating, starting, stopping, resizing, terminating, or changing storage or endpoints.
- After mutation, retain the resource ID and reconcile with a read-only list/status command. Never blindly retry an ambiguous launch.
- Verify the actual workload and requested artifacts; a running Pod or ready endpoint is not proof of scientific success.
- Stop idle billable resources. Verify outputs before termination and ask separately before deleting persistent storage.
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.
- 1mo ago First seen · 56 lines · 32 tokens per session scan A d7c6b62089b4
runpod-gpu-cloud is a skill published in the GitHub repository synthetic-sciences/openscience (4,121 stars, last pushed 2d ago), licensed Apache-2.0. It adds 32 tokens to every session and 750 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
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