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.
git clone --depth 1 https://github.com/jimmc414/KosmosWrote 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/plugins/jimmc414/kosmos/scientific-skills)<a href="https://agentmods.dev/plugins/jimmc414/kosmos/scientific-skills"><img src="https://agentmods.dev/badge/plugins/jimmc414/kosmos/scientific-skills/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/plugins/jimmc414/kosmos/scientific-skills"><img src="https://agentmods.dev/badge/plugins/jimmc414/kosmos/scientific-skills.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
scientific-skills 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 2mo 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What it installs
The manifest is a name and a version. 119 skills travel with it, and installing the plugin installs all of them — 7,207 tokens a session between them. Each is measured on its own page, and each can be installed alone.
- Skill geo-database A 47 tokens
- Skill gget A 79 tokens
- Skill scientific-visualization A 45 tokens
- Skill clinpgx-database A 45 tokens
- Skill datamol A 67 tokens
- Skill deeptools A 51 tokens
- Skill gwas-database A 50 tokens
- Skill histolab A 91 tokens
- Skill hypogenic A 65 tokens
- Skill literature-review A 86 tokens
- Skill pymatgen A 38 tokens
- Skill rdkit A 80 tokens
- Skill scientific-critical-thinking A 40 tokens
- Skill seaborn A 38 tokens
- Skill shap A 109 tokens
- Skill statistical-analysis A 42 tokens
- Skill statsmodels A 41 tokens
- Skill string-database A 44 tokens
- Skill torch-geometric A 41 tokens
- Skill uspto-database A 40 tokens
- Skill zarr-python A 42 tokens
- Skill alphafold-database A 55 tokens
- Skill biopython A 76 tokens
- Skill cellxgene-census A 47 tokens
- Skill clinicaltrials-database A 47 tokens
- Skill dask A 39 tokens
- Skill deepchem A 45 tokens
- Skill diffdock A 40 tokens
- Skill exploratory-data-analysis A 89 tokens
- Skill fda-database A 43 tokens
- Skill flowio A 47 tokens
- Skill lamindb A 135 tokens
- Skill molfeat A 47 tokens
- Skill opentargets-database A 40 tokens
- Skill opentrons-integration A 49 tokens
- Skill paper-2-web A 78 tokens
- Skill peer-review A 35 tokens
- Skill perplexity-search A 99 tokens
- Skill pubchem-database A 49 tokens
- Skill pubmed-database A 58 tokens
- Skill pufferlib A 83 tokens
- Skill pydeseq2 A 45 tokens
- Skill pyhealth A 109 tokens
- Skill pymc-bayesian-modeling A 48 tokens
- Skill pymoo A 46 tokens
- Skill reportlab A 38 tokens
- Skill scientific-writing A 46 tokens
- Skill scikit-bio A 54 tokens
- Skill scikit-learn A 68 tokens
- Skill scikit-survival A 91 tokens
- Skill torchdrug A 60 tokens
- Skill umap-learn A 43 tokens
- Skill zinc-database A 47 tokens
- Skill aeon A 74 tokens
- Skill anndata A 67 tokens
- Skill astropy A 84 tokens
- Skill benchling-integration A 44 tokens
- Skill biorxiv-database A 52 tokens
- Skill chembl-database A 46 tokens
- Skill clinvar-database A 45 tokens
- Skill cobrapy A 38 tokens
- Skill dnanexus-integration A 49 tokens
- Skill esm A 86 tokens
- Skill kegg-database A 60 tokens
- Skill matplotlib A 43 tokens
- Skill medchem A 39 tokens
- Skill metabolomics-workbench-database A 53 tokens
- Skill modal A 46 tokens
- Skill networkx A 85 tokens
- Skill neurokit2 A 96 tokens
- Skill openalex-database A 76 tokens
- Skill pydicom A 110 tokens
- Skill pytdc A 41 tokens
- Skill scanpy A 51 tokens
- Skill scholar-evaluation A 81 tokens
- Skill simpy A 56 tokens
- Skill sympy A 98 tokens
- Skill xlsx A 32 tokens
- Skill biomni A 82 tokens
- Skill bioservices A 72 tokens
- Skill cosmic-database A 39 tokens
- Skill datacommons-client A 77 tokens
- Skill drugbank-database A 84 tokens
- Skill ensembl-database A 45 tokens
- Skill fluidsim A 69 tokens
- Skill geniml A 89 tokens
- Skill get-available-resources A 115 tokens
- Skill gtars A 50 tokens
- Skill hmdb-database A 46 tokens
- Skill labarchive-integration A 41 tokens
- Skill latchbio-integration A 45 tokens
- Skill omero-integration A 39 tokens
- Skill pdb-database A 49 tokens
- Skill polars A 40 tokens
- Skill pylabrobot A 98 tokens
- Skill pysam A 47 tokens
- Skill scientific-brainstorming A 35 tokens
- Skill stable-baselines3 A 87 tokens
- Skill tooluniverse A 112 tokens
- Skill arboreto A 66 tokens
- Skill denario A 69 tokens
- Skill ena-database A 43 tokens
- Skill gene-database A 49 tokens
- Skill hypothesis-generation A 33 tokens
- Skill markitdown A 101 tokens
- Skill matchms A 40 tokens
- Skill pathml A 102 tokens
- Skill pdf A 29 tokens
- Skill pytorch-lightning A 65 tokens
- Skill scvi-tools A 81 tokens
- Skill uniprot-database A 66 tokens
- Skill vaex A 99 tokens
- Skill pyopenms A 86 tokens
- Skill transformers A 63 tokens
- Skill pptx B 30 tokens
- Skill etetoolkit B 46 tokens
- Skill protocolsio-integration B 85 tokens
- Skill docx B 29 tokens
- Skill reactome-database B 35 tokens
What ships with it
1 file beside marketplace.json#scientific-skills in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 127 lines scan A fb5082302c1c
scientific-skills is a plugin published in the GitHub repository jimmc414/Kosmos (605 stars, last pushed 28d ago), with no licence file. Its token cost is not measured: this kind of file is read by the harness, not the model. 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.
scientific-skills compared with plugins from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| scientific-skillsjimmc414/Kosmos | Plugin | 605 | 28d ago | none | A | — | Claude Code |
| antimicrobial-resistance-scientistK-Dense-AI/scientific-agents | Plugin | 237 | 1mo ago | MIT | A | — | Claude Code |
| catalysis-scientistK-Dense-AI/scientific-agents | Plugin | 237 | 1mo ago | MIT | A | — | Claude Code |
| hyphamycelium-cmbse/mycelium-hypha | Plugin | 12 | yesterday | Apache-2.0 | A | — | Claude Code |
| r2g-skillsShenShan123/r2g-skills | Plugin | 44 | 8d ago | MIT | B | — | Claude Code |
| aremaballarin/ccplugins | Plugin | 4 | 11d ago | MIT | A | — | Claude Code |
| physical-sciencesKalarisLabs/research-agent-skills | Plugin | 105 | today | none | A | — | Claude Code |