anndata

anndata is a skill for Claude Code, Codex from crazymsn/academic-skills. It costs 63 tokens per session (2,749 once invoked), scanned A, a copy of anndata, MIT.

A guide to AnnData, a Python data structure for measurements paired with information about their observations and measured features. It is commonly used for single-cell genomics, where rows may represent cells and columns genes.

In plain words
What is it for?
Use it with .h5ad or Zarr files, single-cell analysis, experimental batches, metadata filtering, and tools such as Scanpy or scvi-tools.
Why use it?
It provides a consistent way to store, read, transform, and combine annotated scientific datasets, including large sparse datasets.

Skill for Claude CodeCodex

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

Good fit Use it with .h5ad or Zarr files, single-cell analysis, experimental batches, metadata filtering, and tools such as Scanpy or scvi-tools.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/crazymsn/academic-skills/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 crazymsn/academic-skills --skill anndata
Clone the repo
git clone --depth 1 https://github.com/crazymsn/academic-skills

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/crazymsn/academic-skills/anndata/github.svg)](https://agentmods.dev/skills/crazymsn/academic-skills/anndata)
Your own site
<a href="https://agentmods.dev/skills/crazymsn/academic-skills/anndata"><img src="https://agentmods.dev/badge/skills/crazymsn/academic-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.

agentmods 80×15 button for anndata

Your own site · 80×15
<a href="https://agentmods.dev/skills/crazymsn/academic-skills/anndata"><img src="https://agentmods.dev/badge/skills/crazymsn/academic-skills/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 2,749 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 88% 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 $0.02749
Opus 5 $0.00032 $0.01375
Sonnet 5 $0.00013 $0.00550
Haiku 4.5 $0.00006 $0.00275

Measured 10d ago against content hash cd4620ee3c3e, 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

88% 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.

academic-skills/anndata/SKILL.md · 397 lines

How it starts

The opening of the file, as written. The whole thing — 397 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 · 397 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 · 397 lines · 63 tokens per session scan A cd4620ee3c3e

Subscribe to this mod's changes

anndata is a skill published in the GitHub repository crazymsn/academic-skills (22 stars, last pushed 3mo ago), licensed MIT. It adds 63 tokens to every session and 2,749 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to anndata, differing in 87 lines, and is treated as a copy.

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