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Analyze a lab report

mediora__analyze_lab_pdf

Upload a lab-report PDF or scan (by HTTPS URL) and trigger Mediora.AI's full Vision + analysis pipeline. Returns a pending test id the client can poll. The URL must be https, must resolve to a public IP (no localhost / cloud-metadata / private LAN), and the file must be PDF / JPEG / PNG ≤ 10 MB. Redirects are not followed — pass the final URL.

Input Schema

NameRequiredDescriptionDefault
file_urlYesPublic HTTPS URL of the lab-report PDF to analyze.
languageNoPreferred language for the analysis output. Defaults to 'en'.
bearer_tokenYesMediora.AI patient JWT (see mediora__whoami).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Goes well past annotations (readOnlyHint=false, openWorldHint=true, idempotentHint=false) by disclosing the async non-terminal response, the SSRF-style URL restrictions (no localhost, cloud-metadata, private LAN), no redirect following, and the 10 MB / MIME limits. These are exactly the failure modes an agent would otherwise hit blindly.

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?

Four short sentences, front-loaded with purpose and return contract, then constraints. Every clause carries operational information; nothing is redundant with the schema or annotations.

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?

For a mutation-flavoured ingestion tool with no output schema, the description covers the async return, the size/MIME/network acceptance criteria, and points at mediora__whoami (via schema) for the token. An agent can call it and handle the result without further 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 coverage is 100%, so the baseline is 3; the description adds real semantics beyond the schema's 'Public HTTPS URL' by specifying scheme, reachability, size and MIME constraints, plus redirect behaviour. It adds nothing about bearer_token or language, which the schema already documents.

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 (upload + trigger analysis) on a specific resource (lab-report PDF/scan) and names the async contract: it returns a pending test id the client can poll. No sibling in the list performs ingestion, so it is unambiguous against explain_*/list_*/get_test_details.

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

Usage Guidelines4/5

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

Describes the invocation context (HTTPS URL, public-IP reachable, PDF/JPEG/PNG ≤10MB, no redirects) and implies the follow-up action of polling the returned test id. It never names the polling sibling (get_test_details) or states when not to use this tool, so it stops short of a 5.

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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