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 lambda-labsgit 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/lambda-labs)<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/lambda-labs"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/lambda-labs/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/lambda-labs"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/lambda-labs.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 | $0.00897 |
| Opus 5.5 | $0.00013 | $0.00359 |
| Sonnet 5.5 | $0.00006 | $0.00179 |
| Haiku 4.5 | $0.00003 | $0.00090 |
Grade A, and why
lambda-gpu-cloud scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
dependencies: [curl, ssh] How it starts
The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lambda Cloud
Use this skill for Lambda Cloud instance discovery and lifecycle planning. Do not invent a Lambda-native CLI: the supported automation contract used here is Lambda's documented HTTPS Cloud API.
OpenScience credential boundary
- A key saved in Customize > Compute > Lambda is encrypted control-plane data. It is not exported into Bash, Task, notebooks, kernels, plugins, or MCP servers.
- Use
provider_computewithlist_resources,resource_status, orlist_availabilityfor live instance and capacity reads.accountis the same reviewed instance-list request used by Test connection. - Test connection must approve an administrator-managed, non-writable
curlexecutable; the macOS system/usr/bin/curlsatisfies that boundary. User-owned replacements are rejected. - The bearer header is supplied to the approved
curlover stdin, so the key is not placed in argv or a temporary file. - OpenScience updates
last_usedonly after the API returns success. - Never print, log, persist, or put the key in a URL. The saved credential cannot launch, restart, terminate, or change resources; a generic shell is unauthenticated unless the user configured it separately.
API contract
Use the current API reference before constructing a request:
- Base URL:
https://cloud.lambda.ai/api/v1 - Authentication:
Authorization: Bearer <API key> - Response and request shapes: use the current endpoint schema from the official API documentation
For local user-managed authentication, avoid secrets in shell history. This read-only pattern keeps the header input out of argv:
printf 'Authorization: Bearer %s\n' "$LAMBDA_API_KEY" \
| curl --fail-with-body --silent --show-error \
--request GET \
--url https://cloud.lambda.ai/api/v1/instances \
--header 'accept: application/json' \
--header @-
Do not run that command unless the shell was independently authenticated; a key saved in OpenScience is intentionally unavailable there.
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 · +8 lines 7dd89bab4252
- 1mo ago First seen · 67 lines · 32 tokens per session scan A e2c3640fb12f
lambda-gpu-cloud is a skill published in the GitHub repository synthetic-sciences/openscience (4,082 stars, last pushed yesterday), licensed Apache-2.0. It adds 32 tokens to every session and 897 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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