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Disease semantic similarity index v1.0.0

Use this resource to measure the semantic isolation of disease research

New

  • 495 downloads
  • 225 likes
  • 249 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install disease-semantic-similarity-index

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent retrieves PubMed abstracts from 2000 to 2025 for a list of GBD diseases, computes 768-dimension PubMedBERT embeddings and four semantic equity metrics per disease. You get scores per disease and an interpretation guide.

Mostly picked by

Updated November 2, 2026

Card for the “Disease semantic similarity index” skill

Details

Generates with
Your agent's model
Licence
MIT

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What you get

  • SKILL.md : retrieval pipeline, embeddings and index calculation
  • SKILL.md : sample output and interpretation guide

Good fit for

  • You compare research effort across several diseases
  • You are looking for under-explored areas in health research

Not for

    Tags

    • research
    • PubMed
    • embeddings

    About

    You say

    “Compute the semantic similarity index for the GBD list of cardiovascular diseases.”

    Card for the “Disease semantic similarity index” skill

    Skill published by Manuel Corpas under the MIT license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to measure the semantic isolation of disease research
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md6.3 KB

    Origin and licence

    Listed unmodified

    Author
    Manuel Corpas
    Source
    github.com/aaaaqwq/agi-super-team/tree/4c7b20bc52ad8d4a89fa3f5185abc455ef9248de/skills/claw-semantic-sim
    Licence
    MIT

    Notice

    « claw-semantic-sim » (Manuel Corpas, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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