Scientific Agent Skills is a collection of reusable procedures that give AI agents capabilities for scientific research across areas such as biology, chemistry, medicine, and drug discovery. It is used by researchers and by people building AI scientist workflows with compatible coding agents. The catalogue contains many of the project's skills and supporting 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 K-Dense-AI/scientific-agent-skills --skill anndatagit clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skillsWrote 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/k-dense-ai/scientific-agent-skills/anndata)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/anndata"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/anndata/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/k-dense-ai/scientific-agent-skills/anndata"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/anndata.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00061 | $0.04161 |
| Opus 5.5 | $0.00024 | $0.01664 |
| Sonnet 5.5 | $0.00012 | $0.00832 |
| Haiku 4.5 | $0.00006 | $0.00416 |
Grade A, and why
anndata 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 14d 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- anndata — 100% identical, 151 lines differ
- anndata — 100% identical, 149 lines differ
- anndata — 100% identical, 151 lines differ
- anndata — 100% identical, 151 lines differ
- anndata — 92% identical, 133 lines differ
- anndata — 91% identical, 188 lines differ
- anndata — 89% identical, 188 lines differ
- anndata — 89% identical, 188 lines differ
How it starts
The opening of the file, as written. The whole thing — 475 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AnnData
Overview
AnnData is a Python package for handling annotated data matrices, storing experimental measurements (X) alongside observation metadata (obs), variable metadata (var), and multi-dimensional annotations (obsm, varm, obsp, varp, uns). Originally designed for single-cell genomics through Scanpy, it now serves as a general-purpose framework for any annotated data requiring efficient storage, manipulation, and analysis.
When to Use This Skill
Use this skill when:
- Creating, reading, or writing AnnData objects
- Working with h5ad, zarr, or other genomics data formats
- Performing single-cell RNA-seq analysis
- Managing large datasets with sparse matrices or backed mode
- Concatenating multiple datasets or experimental batches
- Subsetting, filtering, or transforming annotated data
- Integrating with scanpy, scvi-tools, or other scverse ecosystem tools
Installation
Targets AnnData 0.13.4 (current PyPI release reviewed 2026-09-30), requiring Python 3.12+. Small synthetic checks cover dense/sparse matrices, native I/O, metadata, concatenation, and lazy reads. File paths, biological analysis, remote stores, and third-party integration examples are illustrative unless stated otherwise.
uv pip install "anndata==0.13.4"
# Lazy I/O and dask-backed operations
uv pip install "anndata[dask,lazy]==0.13.4"
Use unpinned installs only when intentionally tracking the latest compatible release.
Current API notes:
- Use
anndata.iofor non-nativeread_*andwrite_*helpers. Top-levelanndata.read_h5adandanndata.read_zarrremain supported. - Use
ad.concat;AnnData.concatenate()was removed in 0.13. Avoid oldad.read, deprecatedAnnData.*_keys()helpers andanndata.__version__; prefer explicit readers, mapping.keys(), andimportlib.metadata.version("anndata"). - In 0.13,
.Xis alsolayers[None]; layer iteration includesNone. Usekey is not Nonewhen selecting named layers. View.Xwrites now use copy-on-write. - Zarr v3 and automatic sharding are the defaults; the Python dependency is Zarr >=3. Dense H5AD
Xremains writable withbacked="r+", but backed sparse item assignment is unsupported in 0.13. AnnLoaderand Loom reading/writing are deprecated.AnnCollectionand other experimental APIs need the caveats in the references.
What ships with it
5 files beside SKILL.md 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.
- 14d ago Changed · +20 lines · -2 tokens per session a619c4088e1b
- 15d ago Changed · +7 lines 3057c2384f1f
- 1mo ago Changed · +16 lines 394e98bdcd8e
- 1mo ago First seen · 432 lines · 63 tokens per session scan A c7c326d42419
anndata is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (50,453 stars, last pushed today), licensed MIT. It adds 61 tokens to every session and 4,161 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 2026-08-30.
Other skills, from other repositories
discovery-toolbox
A routed repertoire of 90 scientific thinking operators for biological research agents - visual reasoning, detectability and information budgets, search reframing, causal identification, competing explanations, observation and selection processes, pipeline artifact diagnosis, effort allocation, and confirmation…
discovery-director
Operate as a research director making original discoveries from a given biological question and dataset. Use when the task is open-ended scientific research, exploring omics or experimental data for findings, hypothesis generation and testing, screening a large candidate space of genes, variants, features or…
bio-interdomain-hgt
Detect and polarize interdomain horizontal gene transfer with reciprocal hits, genomic context, and gene trees. Use for virus-host gene exchange, endogenous viral elements, or donor direction.
csag-extraction
Extract a Conditional Scientific Argumentation Graph and grounded Q&A from a manuscript. Use when representing assertions, contexts, evidence links, and inference steps in machine-readable form.
notebooks
Author, run and convert marimo or Jupyter notebooks. Use when delivering an analysis notebook executed end to end with figures embedded.
bio-annotation
Annotate proteins with functions, domains, and homology-based taxonomy. Use when assigning functional or taxonomic labels to proteins from genomes, contigs, or MAGs.