Skip to content
TrustedSkillsbeta
Back to all skills

Metabolomics Workbench Database

Listed
davila7·vlatest·database·MIT

Access and query Davila7's curated metabolomics workbench database for compound IDs, spectral data, and experimental contexts.

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 davila7/claude-code-templates --skill metabolomics-workbench-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

davila7

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.

Nobody has reviewed this code. TrustedSkills indexes and links skills; it does not audit, run or scan them. A skill runs with whatever access you give your agent — read the source before you install it.

Automated safety checks

scanned

We could not read this skill's source, so none of the checks below were run.

Not scanned. none of the 457 skills in the repository match this slug — it was most likely renamed or removed upstream after the registry indexed it Source recorded as davila7/claude-code-templates.
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

The metabolomics-workbench-database skill provides AI agents with access to the Metabolomics Workbench, a public repository for metabolomics data. It enables agents to query, retrieve, and analyze large-scale datasets related to metabolic profiles from human studies.

When to use it

  • Retrieving specific metabolite concentration data from published clinical trials.
  • Analyzing correlations between metabolic markers and disease states using existing public records.
  • Extracting experimental metadata regarding sample collection methods and processing protocols.
  • Comparing results across multiple studies to identify consistent biological patterns.

Key capabilities

  • Direct querying of the Metabolomics Workbench API.
  • Retrieval of study-level metadata including design, population, and analytical methods.
  • Access to raw metabolite intensity data for statistical analysis.
  • Filtering datasets by specific conditions such as disease type or demographic variables.

Example prompts

  • "Search the Metabolomics Workbench for studies involving Type 2 diabetes and extract peak intensities for lipids."
  • "Retrieve metadata for all studies that used NMR spectroscopy to analyze plasma samples from elderly populations."
  • "Compare metabolite profiles between control and treatment groups in studies published after 2020."

Tips & gotchas

Ensure your AI agent has valid API credentials or handles rate limiting gracefully, as public repositories often impose query restrictions. Always verify that the retrieved data aligns with the specific experimental protocols described in the study metadata before drawing conclusions.