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Tooluniverse Spatial Transcriptomics

Checked
mims-harvard·vlatest·other·Apache-2.0

This skill leverages ToolUniverse to analyze spatial transcriptomics data, revealing gene expression patterns within tissue structures for deeper biological insights.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add mims-harvard/tooluniverse --skill tooluniverse-spatial-transcriptomics -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

mims-harvard

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Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned mims-harvard/tooluniverse at f5c37eebeb.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
f5c37eebeb
Manifest
skills/tooluniverse-spatial-transcriptomics/SKILL.md
Scanned
9 files, 2,088 lines
Copies in repo
3 — all of them scanned
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
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About this skill

The tooluniverse-spatial-transcriptomics skill enables AI agents to analyze spatial transcriptomics datasets, mapping gene expression patterns directly onto tissue coordinates. It processes complex biological data to reveal how cellular interactions vary across specific anatomical regions within a sample.

When to use it

  • Investigating tumor microenvironments to identify distinct cell populations based on their physical location.
  • Analyzing brain tissue sections to correlate gene activity with specific neural structures.
  • Studying developmental biology by tracking how gene expression shifts across growing tissues.
  • Validating single-cell RNA sequencing results by adding spatial context to cellular data.

Key capabilities

  • Ingests and processes raw spatial transcriptomics data files.
  • Maps gene expression levels onto 2D or 3D tissue coordinates.
  • Identifies spatially variable genes within defined regions of interest.
  • Visualizes cellular neighborhoods and interaction patterns.

Example prompts

  • "Analyze this breast cancer tissue sample to identify clusters of immune cells surrounding tumor regions."
  • "Map the expression of neurodevelopmental markers across different layers of the cerebral cortex."
  • "Detect spatially variable genes in this liver section that correlate with fibrosis zones."

Tips & gotchas

Ensure your input data includes accurate coordinate metadata, as the tool relies on precise spatial alignment to generate meaningful maps. While effective for pattern recognition, interpret results alongside traditional histology to confirm biological context.