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get_mouse_gene

Resolve mouse gene symbols, MGI IDs, or Ensembl IDs to MGI identifiers and gene details for Mus musculus. Use it to cross-reference mouse genes across databases.

Instructions

Resolve mouse gene details and MGI identifiers (Mus musculus).

Args: query: Mouse gene symbol (e.g. 'Trp53') or MGI ID (e.g. 'MGI:98834') or Ensembl ID.

Returns: JSON string containing the resolved mouse gene entity with MGI identifier.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.7.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It discloses that this is a resolution/lookup operation returning a JSON string containing the gene entity and MGI identifier, which is the minimum viable disclosure, but says nothing about ambiguity handling, multi-match behavior, or error cases.

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?

Front-loaded purpose sentence followed by tight Args/Returns blocks with no filler. Every line carries information an agent needs, and the example values are compact and useful.

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?

An output schema exists, so return values needn't be fully explained, and the single parameter is well covered. The one real gap is guidance on when to choose this over resolve_gene or batch_resolve_genes, which for a crowded sibling set leaves an agent guessing.

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 compensate, and it does: it enumerates three accepted identifier forms (gene symbol like 'Trp53', MGI ID like 'MGI:98834', or Ensembl ID). This is genuinely more informative than the bare 'Query' property in the schema.

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

Purpose4/5

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

States a specific verb (resolve) and resource (mouse gene details and MGI identifiers) with an explicit species qualifier (Mus musculus), which implicitly separates it from the human-oriented resolve_gene sibling. However, it never names that sibling, so the differentiation is inferable rather than stated.

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

Usage Guidelines2/5

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

No when-to-use or when-not-to-use guidance is given. The presence of resolve_gene, find_orthologs, and batch_resolve_genes among siblings makes a routing hint valuable, and the description provides none — the query-format notes are input syntax, not usage context.

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