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Gwas Database

Listed
ovachiever·vlatest·database

Access and query ovachiever's GWAS database to identify genetic associations related to ovarian cancer phenotypes.

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 ovachiever/droid-tings --skill gwas-database -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

ovachiever

Taken from the source listing. We haven't verified who controls this account.

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 2 hosts that are neither well-known infrastructure nor declared in the skill's frontmatter: ftp.ebi.ac.uk, www.ebi.ac.uk.

    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.

    Hosts contacted

    www.ebi.ac.ukundeclaredftp.ebi.ac.ukundeclared

    What it found (3 of 4)

    • skills/gwas-database/SKILL.md:282contacts www.ebi.ac.uk
      response = requests.get("https://www.ebi.ac.uk/gwas/rest/api/studies/GCST001234")
    • skills/gwas-database/references/api_reference.md:303contacts www.ebi.ac.uk
      response = requests.get("https://www.ebi.ac.uk/gwas/rest/api/studies/GCST001795")
    • skills/gwas-database/SKILL.md:404contacts ftp.ebi.ac.uk
      wget ftp://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/GCSTXXXXXX/harmonised/GCSTXXXXXX-harmonised.tsv.gz

  • 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 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 ovachiever/droid-tings at 7acd12a754.

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

Commit
7acd12a754
Manifest
skills/gwas-database/SKILL.md
Scanned
2 files, 1,269 lines
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.
What each check looks for →

About this skill

What it does

This skill provides direct access to a specialized database containing Genome-Wide Association Study (GWAS) data focused on ovarian cancer phenotypes. It enables users to retrieve and query specific genetic associations linked to the disease, facilitating research into hereditary risk factors.

When to use it

  • Investigating specific single nucleotide polymorphisms (SNPs) known to correlate with ovarian cancer susceptibility.
  • Analyzing genetic markers to understand the biological pathways involved in ovarian cancer development.
  • Validating existing hypotheses regarding the relationship between specific gene variants and clinical ovarian cancer outcomes.
  • Extracting baseline GWAS statistics for comparative analysis in new cohort studies.

Key capabilities

  • Querying the ovachiever GWAS database for ovarian cancer-specific genetic associations.
  • Identifying significant loci linked to defined ovarian cancer phenotypes.
  • Retrieving structured data on genetic variants relevant to hereditary cancer research.

Example prompts

  • "Query the database for all genetic associations significantly linked to high-grade serous ovarian cancer."
  • "Retrieve the top 10 SNPs identified in this GWAS study that correlate with early-onset ovarian cancer phenotypes."
  • "List the specific gene loci associated with reduced survival rates in ovarian cancer patients found in this dataset."

Tips & gotchas

Ensure you have a clear research question regarding ovarian cancer genetics before querying, as the database is specialized for this specific phenotype. Results are strictly limited to the associations contained within the ovachiever GWAS collection and may not reflect broader genomic databases.