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firm_compliance_history

Create a source-bounded timeline of FDA public records for a medical device firm, covering matched recalls, warning letters, and Form 483 citations with attribution.

Instructions

Build a recent, source-bounded FDA public-record timeline for a device firm: matched recalls, warning letters, and Form 483 citations where exact FEI numbers are available. Product codes are discovered from Constat's AI/ML-device corpus or may be supplied explicitly. Returns attribution and coverage limits with the records; it is not a finding of noncompliance or a prediction of FDA action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum records per source and events in the timeline (default 50).
sinceNoEarliest event date, YYYY-MM-DD. Defaults to five years ago.
firm_nameYesFDA applicant or company name, e.g. 'Medtronic'
fei_numbersNoOptional exact FDA FEI numbers; improves Form 483 attribution.
product_codesNoOptional FDA product-code scope. When omitted, Constat discovers codes from applicant matches in its device corpus.
Behavior4/5

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

No annotations exist, so the description carries full burden. It discloses source-bounded nature, use of FEI numbers, product code discovery, and includes a caveat that it is not a finding of noncompliance. However, it could clarify data freshness or potential delays.

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 concise with three sentences covering purpose, sources, constraints, and disclaimer. No wasted words; key information is front-loaded.

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?

Given 5 parameters and no output schema, the description covers purpose, sources, and limitations. It mentions 'returns attribution and coverage limits' but could elaborate on response format or pagination for completeness.

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%, so baseline is 3. The description adds context about product code discovery from a corpus but does not provide additional specifics for individual parameters beyond what the schema already defines.

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 explicitly states it builds a timeline of FDA records (recalls, warning letters, Form 483) with specific constraints (exact FEI numbers, product code discovery). It clearly distinguishes from sibling tools like device_evidence_lookup which are more general searches.

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 usage for firm compliance history but does not explicitly state when to use this tool versus alternatives like evidence_search or device_postmarket_lookup. No when-not or alternative guidance is 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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