Open Science is a local-first, model-agnostic workbench for reproducible scientific research. Scientists use its AI agents, Python and R execution, data connectors, and traceable outputs for tasks such as literature review, analysis, simulation, and visualization across macOS, Windows, and Linux.
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 aipoch/open-science --skill compute-env-setupgit clone --depth 1 https://github.com/aipoch/open-scienceWrote 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/aipoch/open-science/compute-env-setup)<a href="https://agentmods.dev/skills/aipoch/open-science/compute-env-setup"><img src="https://agentmods.dev/badge/skills/aipoch/open-science/compute-env-setup/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/aipoch/open-science/compute-env-setup"><img src="https://agentmods.dev/badge/skills/aipoch/open-science/compute-env-setup.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00061 | $0.02145 |
| Opus 5.5 | $0.00024 | $0.00858 |
| Sonnet 5.5 | $0.00012 | $0.00429 |
| Haiku 4.5 | $0.00006 | $0.00215 |
Grade A, and why
compute-env-setup 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 — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compute environment setup
Prepare one reproducible environment definition and instructions for one small user-managed host
activation file. Open-Science resolves submitJob(..., { environment: '<name>' }) by sourcing
~/.open-science/environments/<name>.sh before the workload. Existing ~/.openscience/environments/<name>.sh definitions remain readable in place. Before creating an activation, check both names: update the existing definition at its exact location; if both exist, ask the user which to retain. Never create a second activation just to rename the brand. The file contains activation only; it
does not install packages when a job starts.
The environment, package caches, images, and activation file are user-managed durable resources,
not Open-Science-owned components. This Skill may inspect them and prepare exact setup/removal
commands, but must not execute commands that create, replace, or remove those resources. The user
or host administrator runs those commands outside Open-Science and owns their lifecycle. Do not
interpret the ~/.openscience path as app ownership.
Use host.compute only in repl_execute JavaScript. Python and R data kernels do not expose it.
Start from the Session catalog and do not guess a provider id:
const hosts = await host.compute.listHosts()
const selected = hosts.filter((candidate) => candidate.role === 'selected')
const candidates = selected.length > 0 ? selected : hosts
Choose the requested host, or a suitable candidate when the user left the target open. Read its knowledge and probe snapshot before changing it:
const providerId = candidates[0].provider_id
const executionMode = candidates[0].execution_mode
const details = await host.compute.details(providerId, { mode: 'read' })
const compute = host.compute.create(providerId)
If no eligible host exists, or the selected host is unsuitable, explain the concrete blocker. Do not install locally as a substitute for a requested remote environment.
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 Changed · +1 tokens per session c62770e0c318
- 1mo ago First seen · 188 lines · 60 tokens per session scan A b685e78087c5
compute-env-setup is a skill published in the GitHub repository aipoch/open-science (5,355 stars, last pushed today), licensed Apache-2.0. It adds 61 tokens to every session and 2,145 once invoked, about $0.0002 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 2026-09-07.
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