alterlab-anndata

alterlab-anndata is a skill for Claude Code, Codex from roohe/agentic-super-skills. It costs 74 tokens per session (2,775 once invoked), scanned A, original, no licence file.

A data format and Python structure for annotated matrices used in single-cell analysis. It works with .h5ad files and the scverse ecosystem.

In plain words
What is it for?
Use it to read, store, and exchange annotated single-cell data in .h5ad files and related analysis workflows.
Why use it?
It gives single-cell datasets a shared way to store measurements together with cell and feature annotations.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it to read, store, and exchange annotated single-cell data in .h5ad files and related analysis workflows.

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

README.md
[![agentmods](https://agentmods.dev/badge/skills/roohe/agentic-super-skills/alterlab-anndata/github.svg)](https://agentmods.dev/skills/roohe/agentic-super-skills/alterlab-anndata)
Your own site
<a href="https://agentmods.dev/skills/roohe/agentic-super-skills/alterlab-anndata"><img src="https://agentmods.dev/badge/skills/roohe/agentic-super-skills/alterlab-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 alterlab-anndata

Your own site · 80×15
<a href="https://agentmods.dev/skills/roohe/agentic-super-skills/alterlab-anndata"><img src="https://agentmods.dev/badge/skills/roohe/agentic-super-skills/alterlab-anndata.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,775 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 unknown No closer match found 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 $0.00074 $0.02775
Opus 5 $0.00037 $0.01388
Sonnet 5 $0.00015 $0.00555
Haiku 4.5 $0.00007 $0.00278

Measured 7d ago against content hash e7a6ab2555c5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

alterlab-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 7d 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.

skills_library/alterlab-anndata/SKILL.md · 400 lines

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.

Read it on GitHub

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. 7d ago First seen · 400 lines · 74 tokens per session scan A e7a6ab2555c5

Subscribe to this mod's changes

alterlab-anndata is a skill published in the GitHub repository roohe/agentic-super-skills (5 stars, last pushed 3mo ago), with no licence file. It adds 74 tokens to every session and 2,775 once invoked, about $0.0004 per session on Opus 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 2026-09-03.

Related

Other skills, from other repositories

jupyter-notebook

Iterative Python via live Jupyter kernel (hamelnb).

NousResearch/hermes-agent · 18 tokens

matlab

Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 42 tokens

bioservices

Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database lookups use gget; for sequence/file manipulation use…

K-Dense-AI/scientific-agent-skills · 73 tokens

pennylane

Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with…

K-Dense-AI/scientific-agent-skills · 98 tokens

cuopt-numerical-optimization-api

LP, MILP, and QP (beta) with cuOpt — Python, C, and CLI. Use when the user is solving LP, MILP, or QP with any cuOpt interface.

NVIDIA/skills · 51 tokens

rocm-kernels

Provides guidance for writing and benchmarking optimized Triton kernels for AMD GPUs (MI355X, R9700) on ROCm, targeting HuggingFace diffusers (LTX-Video, SD3, FLUX) and transformers. Core kernels: RMSNorm, RoPE 3D, GEGLU, AdaLN. Includes XCD swizzle, autotune, diffusers integration patterns, and LTX-Video pipeline…

huggingface/kernels · 93 tokens