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Glama
vor-bot

xyz.crossgrain/epitaxy

by vor-bot

list_drug_recalls

Retrieve FDA drug recalls by classification, company, and limit to assess supplier exposure and supply chain risk.

Instructions

Stiahnutia liekov podla FDA. Filtre: classification, company_id, limit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
company_idNo
classificationNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.3

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations available, the description carries the full burden of behavioral disclosure, but it only states the subject matter and filter names. It does not say the operation is read-only, what output is returned, whether filtering is exact/partial, or how limits apply.

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?

The description is very short and puts the topic first, with the filter list following after. It uses no filler, though the filter section could have been more informative without losing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no annotations, no output schema, and 0% parameter documentation, this is under-specified: the action must be inferred from the tool name, return values are absent, and parameter meanings are unclear. It is enough to know the topic but not enough to invoke the tool confidently.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description needed to explain classification, company_id, and limit. It merely repeats their names under 'Filtre' and adds no formats, allowed values, defaults, or semantics beyond the schema itself.

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?

The description identifies the domain (drug recalls) and the data source (FDA), and the mention of filters indicates a queryable listing operation. It can be told apart from sibling tools like list_drug_shortages by the recall focus, but it never uses an explicit action verb like 'list' or 'return' and is written in Slovak.

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

Usage Guidelines2/5

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

The filter list provides only an implicit hint of how to call the tool; it does not state when to prefer this tool over alternatives such as list_drug_shortages or get_supplier_exposure. There are no usage exclusions, prerequisites, or scenarios provided.

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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