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Glama

resolve_disease

Resolve disease names, synonyms, or MONDO IDs to MONDO Disease Ontology entries, returning matched IDs, definitions, and cross-references for accurate disease mapping.

Instructions

Resolve a disease name, synonym, or MONDO identifier against the MONDO Disease Ontology.

Args: query: Disease name (e.g. 'Li-Fraumeni syndrome', 'Breast cancer'), synonym, or ID ('MONDO:0018875'). limit: Maximum number of matches to return (default: 5).

Returns: JSON string containing the list of resolved disease entities with MONDO IDs, definitions, and cross-references.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.7.0

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the return content (MONDO IDs, definitions, cross-references), but says nothing about matching behavior (exact vs fuzzy), permissions, rate limits, or what happens with zero/ambiguous matches.

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

Conciseness4/5

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

Front-loaded one-line purpose followed by clearly labeled Args and Returns sections; every line earns its place. Slight redundancy in restating return values that an output schema already covers.

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

Completeness4/5

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

For a two-parameter resolution tool with a required query and an existing output schema, the description gives enough to invoke correctly. It could add ambiguity-handling behavior, which is the main remaining gap.

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 description coverage is 0%, so the description must carry parameter meaning, and it does: it explains the query accepts a name, synonym, or MONDO ID with concrete examples, and defines limit as the maximum matches with its default of 5.

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 (resolve) and resource (disease name/synonym/MONDO ID against the MONDO ontology), which clearly separates it from the gene-oriented siblings (resolve_gene, batch_resolve_genes, get_mouse_gene). An agent can distinguish it without opening the schema.

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

Usage Guidelines3/5

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

The description implies when to use it via the query semantics (name, synonym, or ID), but never states exclusions or alternatives such as when to prefer resolve_gene or batch resolution. Usage is inferable but not explicitly guided.

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