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Animal Drug Detail

animal_drug_detail
Read-onlyIdempotent

Full FDA Green Book detail for one approved animal drug application, by application_id (from animal_drug_search). Returns the sponsor, every marketed product under the application with its species, dose form, route, strength and approved dosage/indications, plus the FOI approval summaries — FDA's own plain-English statement of what each original approval and supplement was FOR, with a PDF link. Answers "what was Rimadyl approved for", "what does application 141053 cover", "show me the approval history of this animal drug".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
application_idYesGreen Book applicationId, e.g. 1024 (Rimadyl Caplets). Get it from animal_drug_search — this is NOT the NADA application number.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, openWorld, non-destructive, so the safety profile is covered. The description adds valuable behavioral context by enumerating what is returned (sponsor, products with species/dose form/route/strength, FOI approval summaries, PDF link), which matters since 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?

A single dense paragraph front-loads the purpose, then details returns and example queries. It is slightly long but each clause contributes meaningful information with no filler.

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 one-parameter read tool with no output schema, the description fully describes the lookup key, its source, and the return payload, plus concrete example questions. Nothing an agent needs to call it correctly is missing.

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 baseline is 3, but the description adds meaning by clarifying the id comes from animal_drug_search and explicitly warning it is NOT the NADA application number, a genuine disambiguation the schema also notes.

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 and resource (return full FDA Green Book detail for one approved animal drug application) plus the exact lookup key. It is clearly distinguishable from the sibling animal_drug_search by being the by-id detail pull rather than the search.

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?

It names the source of the required id ('from animal_drug_search'), routing the agent to the right sibling and implying the sequence. It doesn't give explicit when-not conditions, but the context is unambiguous for an id-based detail 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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