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x402Pulse

health_drug_label

FDA drug label lookup: boxed warning, approved indications, contraindications, warnings and drug interactions for any drug, plus brand and generic names, manufacturer and route, as clean structured text from openFDA. Not medical advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
drugYesDrug brand or generic name

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

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 burden. It does disclose useful behavioral context: the data source (openFDA), the return shape (clean structured text) and a safety disclaimer ('Not medical advice'). It omits anything about lookups that return nothing, rate limits, or whether a missing drug is an error.

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?

One dense sentence that front-loads the resource and enumerates the payload, followed by a short disclaimer. Every clause earns its place, though the enumerated field list makes the sentence slightly heavy.

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 single-parameter read tool with no output schema and no annotations, the description is largely self-sufficient: it names the source, the returned fields and a liability caveat. The main missing element is any indication of behavior when the drug is not found.

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 description coverage is 100% and the single 'drug' parameter is documented as 'Drug brand or generic name'. The description's mention of brand and generic names merely echoes the schema rather than adding format, casing or matching-behavior detail, so the baseline of 3 applies.

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 and resource (FDA drug label lookup) and enumerates the exact data returned (boxed warning, indications, contraindications, warnings, interactions, brand/generic names, manufacturer, route). It is clear what the tool does, but it never distinguishes itself from the closely named siblings health_drug_approvals, health_drug_safety and health_drug_shortages.

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?

Usage is implied — look up a drug's label — but there is no explicit when-to-use, no exclusions, and no routing advice against the sibling drug tools (approvals vs. safety vs. label). An agent must infer the boundary itself.

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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