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Search Mammalian Phenotype Terms

search_phenotype_terms
Read-onlyIdempotent

Search mammalian phenotype terms by free-text query to find matching MP IDs and definitions for use in downstream queries.

Instructions

Free-text search over Mammalian Phenotype (MP) term names and definitions (FTS, relevance-ranked). Returns {mp_id, name, definition, score} plus a truncation contract {total, returned, limit, truncated} (widen step in next_commands when truncated). Use this to resolve a phenotype description to an MP id, then find_markers_by_phenotype or get_mp_term. Signature: search_phenotype_terms(query, limit=).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax hits (default 25).
queryYesFree-text phenotype query (e.g. 'small kidney').
Behavior5/5

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

The description adds significant behavioral context beyond annotations (readOnlyHint, idempotentHint, etc.): it discloses that the search is FTS, relevance-ranked, and includes a truncation contract with next_commands. This transparency helps the agent understand search behavior and pagination without contradictions.

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?

The description is concise (4 sentences), front-loaded with the main purpose, and every sentence adds value (usage guidance, truncation details, signature). No redundant or unclear text.

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?

Despite no output schema, the description lists return fields ({mp_id, name, definition, score}) and explains the truncation contract, making the tool's behavior fully understandable. Combined with clear usage guidance and parameter docs, it is contextually complete for an AI agent.

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

Parameters3/5

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

Schema coverage is 100% with clear parameter descriptions. The description reiterates the parameter meaning (e.g., 'query' as free-text) and mentions the default limit, but does not add new semantic information beyond what the schema already provides. Thus, baseline score of 3 is appropriate.

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?

The description clearly states a specific verb 'Free-text search' over 'Mammalian Phenotype (MP) term names and definitions', indicating the resource and action. It distinguishes from sibling tools like find_markers_by_phenotype by explicitly stating the use case and subsequent steps.

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?

The description provides explicit guidance: 'Use this to resolve a phenotype description to an MP id' and suggests subsequent tools (find_markers_by_phenotype, get_mp_term). It also mentions the signature and default limit, leaving no ambiguity about when to invoke this tool.

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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