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Find a drug, gene or topic

find_entities
Read-onlyIdempotent

Use this to find the type and key of what a question names (a drug, supplement or diet, a gene or protein, a biological process, a disease, a biomarker, an organism, a method or a hallmark of aging) before get_entity, list_claims or list_grants. Matches part of a name, a key or a known synonym, case-insensitive, most-studied first, with how many papers involve each. Pass a result's type and key to get_entity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoMatch on name or key, case-insensitive substring.
typeNoEntity type, e.g. intervention, gene, pathway, component, system, method, hallmark, phenotype, organism, tissue, disease, biomarker, mesh.
limitNoResults per page, 1 to 25.
cursorNoOpaque cursor from `pagination.next_cursor` of the previous page. Keep the other parameters the same.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover read-only, idempotent and non-destructive behavior, but the description adds real traits beyond them: case-insensitive substring and synonym matching, 'most-studied first' ranking, and that each result carries a paper count. These are useful behavioral disclosures the structured fields don't provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, all earning their place, front-loaded with the 'Use this to...' trigger. No redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, yet the description covers what the tool returns (type, key, paper counts), the ordering, the matching semantics, and the downstream chaining. With annotations covering the safety profile, an agent has everything needed to call and use it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3; the description slightly exceeds it by noting that q matches 'a known synonym' (the schema only mentions name or key) and by explaining that a result's type and key feed into get_entity. It does not add further syntax or format detail for limit/cursor.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (find) and resource (entity types: drug, gene, process, disease, etc.) and explicitly scopes it as resolving a name to a type and key. It names the sibling tools that follow it (get_entity, list_claims, list_grants), so the agent can distinguish it from them without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says when to use it: resolving what a question names before get_entity, list_claims or list_grants. Names the alternatives/downstream tools and the workflow position, leaving little to inference, though it lacks a negative exclusion statement.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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