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Compute triage

infermedica_triage
Read-only

Recommend a triage level (emergency_ambulance | emergency | consultation_24 | consultation | self_care) plus any serious/emergency observations, given the evidence. Non-mutating computation. Engine API: POST /triage.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ageYesPatient age, e.g. { value: 30 } or { value: 6, unit: 'month' }.
sexYesPatient biological sex.
extrasNo
dev_modeNoIf true, mark the request as test traffic → sends the `Dev-Mode: true` header.
evidenceNoList of observed evidence (symptoms / risk factors / lab tests) and their states.
model_idNoOptional medical model id → sent as the `Model-Id` request header.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations give readOnlyHint=true and the description reinforces it with 'Non-mutating computation', clarifying that the POST is a computation rather than a write. It also discloses the return payload (triage level plus serious/emergency observations), which matters because there is no output schema.

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 with the outcome and its enumerated values, followed by the non-mutation note and a compact engine reference. Every sentence earns its place, though the raw endpoint ('POST /triage') is slightly incidental.

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 6-parameter nested-object tool with no output schema, the description usefully names the returned triage level and observations. It stops short of clarifying required-parameter interaction (sex/age) or how partial evidence affects results.

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 83%, so the schema already documents age, sex, evidence, extras, dev_mode, and model_id. The description adds no syntax or format detail beyond the schema and only hints that 'evidence' drives the result. Baseline 3 applies.

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 ('Recommend a triage level') plus the exact enumeration of possible outputs, and names the resource (triage). It is clearly separable from sibling infermedica_diagnosis and the rest of the get/list tools.

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 phrase 'given the evidence' implies a precondition (evidence must already exist, e.g. from infermedica_parse/suggest) but never states when to pick triage over diagnosis or recommend_specialist. Usage is only implied.

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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