Aging and Senescence Research (ToolUniverse Claude Skill)

A ToolUniverse agent skill for geroscience questions: it places a gene or pathway within the aging-hallmarks framework, assembles genetic and pathway evidence, and looks for senolytic or geroprotector opportunities.

   
Type Claude Skill (one of ToolUniverse’s pre-built agent skills)
Supplier Zitnik Lab, Harvard Medical School
Availability GA — part of the ToolUniverse skills collection (skills/tooluniverse-aging-senescence/)
Pricing Free / OSS (Apache-2.0); OpenGenes, GWAS Catalog, Open Targets, KEGG, STRING and PubMed are free public resources
Capabilities Read-only — drives ToolUniverse tool calls; no data writes

How to install

This skill calls ToolUniverse tools, so the ToolUniverse MCP server must be installed first (see the ToolUniverse page). Simplest registration:

claude mcp add --transport stdio tooluniverse -- uvx tooluniverse

Then add the skills:

  • Claude Code — install the whole skill collection (the skill resolves as tooluniverse-aging-senescence): 
    npx skills add mims-harvard/ToolUniverse
  • Manual / other agents — copy just this skill directory into your skills folder: 
    git clone https://github.com/mims-harvard/ToolUniverse
cp -r ToolUniverse/skills/tooluniverse-aging-senescence ~/.claude/skills/

    (replace ~/.claude/skills/ with your agent’s skills directory if you are not using Claude Code/Desktop.)

The skill sets disable-model-invocation: true upstream, so invoke it explicitly (e.g. ask Claude to “use the aging and senescence skill”) rather than relying on automatic dispatch.

What it does

Runs a seven-phase geroscience workflow:

  1. Query parsing — classifies the question as being about an aging gene, a senescence marker, an age-related disease, or a drug, and routes accordingly.
  2. Hallmarks classification — maps the subject onto the twelve hallmarks-of-aging framework.
  3. Genetic evidence — OpenGenes_get_gene / OpenGenes_search_genes for curated aging-gene records with mechanism and study counts, plus gwas_get_snps_for_gene and gwas_search_associations for longevity and age-related-disease loci, and model-organism lifespan data.
  4. Pathway analysis — KEGG_get_pathway_genes and kegg_search_pathway for senescence, autophagy, telomere and epigenetic pathways, with STRING interaction context.
  5. Senolytic / geroprotector discovery — the drug layer, covering the established senolytics (dasatinib + quercetin, fisetin, navitoclax) and OpenTargets_get_associated_targets_by_disease_efoId for aggregated disease-target evidence.
  6. Literature and clinical context — PubMed_search_articles.
  7. Interpretation — an evidence-graded report that explicitly separates correlative findings from causal ones established by knockout or intervention.

Covered subject matter includes senescence markers (p16/CDKN2A, SASP, SA-β-gal), epigenetic clocks, telomere biology, longevity GWAS and centenarian genetics.

Primary use cases: senescence-pathway analysis, age-related disease genetics, senolytic target discovery, centenarian-genetics queries.

Notes

It is a reasoning layer over ToolUniverse; without the MCP server registered, the tool calls fail. The correlative-versus-causal distinction is the point of the skill — a gene that merely changes expression with age is reported as such and not promoted to a target.

For the safety read on any target this surfaces, follow with Gene Liability Evaluation; for the underlying resources see GWAS Catalog, KEGG, Open Targets, STRING and PubMed. ToolUniverse ships ~68 such skills; other workflows are catalogued separately.

Sources

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