anndata

anndata is a skill for Claude Code, Codex from Lord1Egypt/scientific-agent-toolkit. It costs 63 tokens per session (2,759 once invoked), scanned A, a copy of anndata, MIT.

A Python data structure for storing measurements together with labels and related information. It is commonly used for single-cell genomics, where each row may represent a cell and each column a gene, and it can be saved in formats such as .h5ad or zarr.

In plain words
What is it for?
Use it to create, read, write, filter, transform, or combine annotated datasets. It connects with tools such as Scanpy and other scverse packages for single-cell analysis.
Why use it?
It keeps the measurements, cell labels, gene details, and additional analysis results together instead of scattering them across separate files. It also supports large or sparse datasets and combining experimental batches.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to create, read, write, filter, transform, or combine annotated datasets. It connects with tools such as Scanpy and other scverse packages for single-cell analysis.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lord1egypt/scientific-agent-toolkit/anndata
Install

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.

Any agent
npx skills add Lord1Egypt/scientific-agent-toolkit --skill anndata
Clone the repo
git clone --depth 1 https://github.com/Lord1Egypt/scientific-agent-toolkit

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for anndata

README.md
[![agentmods](https://agentmods.dev/badge/skills/lord1egypt/scientific-agent-toolkit/anndata/github.svg)](https://agentmods.dev/skills/lord1egypt/scientific-agent-toolkit/anndata)
Your own site
<a href="https://agentmods.dev/skills/lord1egypt/scientific-agent-toolkit/anndata"><img src="https://agentmods.dev/badge/skills/lord1egypt/scientific-agent-toolkit/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.

agentmods 80×15 button for anndata

Your own site · 80×15
<a href="https://agentmods.dev/skills/lord1egypt/scientific-agent-toolkit/anndata"><img src="https://agentmods.dev/badge/skills/lord1egypt/scientific-agent-toolkit/anndata.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 63 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,759 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 91% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00063 $0.02759
Opus 5 $0.00032 $0.01380
Sonnet 5 $0.00013 $0.00552
Haiku 4.5 $0.00006 $0.00276

Measured 10d ago against content hash 3203fd107ade, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

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 10d 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.

Origin

This is a copy

91% identical to anndata — 87 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

scientific-skills/anndata/SKILL.md · 399 lines

How it starts

The opening of the file, as written. The whole thing — 399 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

uv pip install anndata

# With optional dependencies
uv pip install anndata[dev,test,doc]

Quick Start

Creating an AnnData object

import anndata as ad
import numpy as np
import pandas as pd

# Minimal creation
X = np.random.rand(100, 2000)  # 100 cells × 2000 genes
adata = ad.AnnData(X)

# With metadata
obs = pd.DataFrame({
    'cell_type': ['T cell', 'B cell'] * 50,
    'sample': ['A', 'B'] * 50
}, index=[f'cell_{i}' for i in range(100)])

var = pd.DataFrame({
    'gene_name': [f'Gene_{i}' for i in range(2000)]
}, index=[f'ENSG{i:05d}' for i in range(2000)])

adata = ad.AnnData(X=X, obs=obs, var=var)

Reading data

# Read h5ad file
adata = ad.read_h5ad('data.h5ad')

# Read with backed mode (for large files)
adata = ad.read_h5ad('large_data.h5ad', backed='r')

# Read other formats
adata = ad.read_csv('data.csv')
adata = ad.read_loom('data.loom')
adata = ad.read_10x_h5('filtered_feature_bc_matrix.h5')

Writing data

# Write h5ad file
adata.write_h5ad('output.h5ad')

# Write with compression
adata.write_h5ad('output.h5ad', compression='gzip')

# Write other formats
adata.write_zarr('output.zarr')
adata.write_csvs('output_dir/')

Read the full file on GitHub · 399 lines

Files

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.

Changes

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.

  1. 10d ago First seen · 399 lines · 63 tokens per session scan A 3203fd107ade

Subscribe to this mod's changes

anndata is a skill published in the GitHub repository Lord1Egypt/scientific-agent-toolkit (3 stars, last pushed 3mo ago), licensed MIT. It adds 63 tokens to every session and 2,759 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to anndata, differing in 87 lines, and is treated as a copy.

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