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Glama

epitaxy

get_supplier_exposure

The join: a federal contract whose supplier has an FDA shortage or recall. Every row carries company_name, confidence (exact, probable or weak) and match_method. A cross source join is NEVER exact, because FDA and USAspending share no identifier. The claim is: this government supplier has an active FDA shortage or recall. It does NOT claim that this contract delivers that drug. Without a key you get exact and probable matches only, at most 20 rows, without the evidence field.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
award_idNofederal award identifier
company_idNo
min_confidenceNoweak needs a paid key

Schema Changelog

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

  1. Changed2 schema fields changed
    • addedInput schema / properties / award_id / description
      Added value: +"federal award identifier"
    • addedInput schema / properties / min_confidence / description
      Added value: +"weak needs a paid key"
  2. First observed

TDQS

A4.2/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and does it well. It discloses that the join is never exact, explains the absence of a shared identifier, clarifies the claim boundary, and states the row limits and evidence-field behavior without a key.

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 dense but efficient, with every sentence contributing a distinct piece of information. It front-loads the core purpose and then adds necessary caveats without redundancy or filler.

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?

Despite having no output schema or annotations, the description explains row fields, confidence semantics, key requirements, row limits, and the non-causal nature of the claim. It is largely complete for selecting and invoking the tool, though the undocumented company_id and limit parameters remain a minor gap.

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?

The description adds valuable context for min_confidence by explaining exact/probable/weak levels and the paid-key constraint. However, it does not clarify the meaning or interaction of company_id and limit, and schema coverage is only 50%, so the description only partially compensates for missing parameter documentation.

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 defines the tool as a cross-source join between federal contracts and FDA shortages/recalls. It distinguishes the resource and claim precisely, and the explicit 'does NOT claim that this contract delivers that drug' makes its scope unmistakable compared to sibling list tools.

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?

The description implies when to use the tool by defining what it returns, but it does not explicitly compare it to siblings or state when to choose it over alternatives. The key-dependent behavior provides some context for usage decisions, but no direct when/when-not guidance is given.

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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