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Glama

Drug recalls and shortages

recalls_shortages
Read-onlyIdempotent

Check FDA recalls and shortages for a drug using its name or NDC, returning status, reason, class, and date to assess safety.

Instructions

FDA drug recalls (class, reason, status, date, product) and shortage records (status, company, reason) for a drug, newest first, from openFDA.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
drugYesDrug name or NDC

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
drugYes
recalls_totalYes
shortages_totalYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds a behavioral detail: results are 'newest first' and sourced from openFDA. It does not discuss rate limits or authentication, but given the annotations cover the read-only nature, this is adequate.

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 a single, efficient sentence that front-loads the core function and includes the key fields returned and the ordering. No filler or redundant phrasing; it is appropriately sized for a one-parameter tool.

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?

The tool has an output schema (per context signals), so the description does not need to explain return values. It covers the data source, the type of records (recalls and shortages), the fields, and the ordering. This is complete for the tool's complexity.

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% – the parameter 'drug' is described as 'Drug name or NDC'. The description merely repeats that it is 'for a drug' and adds no additional syntax or format details. Since the schema carries the full semantic load, a baseline 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 the tool's purpose: it retrieves FDA drug recalls (with class, reason, status, date, product) and shortage records (status, company, reason) for a given drug, ordered newest first. It uses a specific verb ('recalls' and 'shortages') and resource (drug), and distinguishes it from sibling tools like find_drug or label_section by specifying the domain.

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?

The description provides clear context: it is for a specific drug, and it returns both recalls and shortages. It implies when to use it (when you need recall or shortage information for a drug), but it does not explicitly mention alternatives or when not to use it. This is a minor gap, as the purpose is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.