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cyntrica

Gov Data MCP

by cyntrica

open_payments_ownership

Read-only

Identify doctors with ownership stakes in pharmaceutical or device companies to uncover potential conflicts of interest. Search by doctor, company, state, or year.

Instructions

Search Open Payments OWNERSHIP data — doctors with ownership or investment stakes in pharma/device companies. The deepest form of conflict of interest. Shows which doctors have financial interests in the companies whose products they prescribe.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoYear (auto-discovers latest if omitted)
limitNoMax results (default 20)
stateNoTwo-letter state: 'CA', 'WA'
doctorNoDoctor last name
companyNoCompany name: 'Pfizer', 'Johnson & Johnson'
Behavior3/5

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

The annotation already declares readOnlyHint=true, so the description does not need to cover safety. It adds qualitative context about the nature of ownership data ('deepest form of conflict of interest') but does not disclose additional behavioral traits such as result format, pagination, or filtering behavior beyond what the schema descriptions provide.

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 compact: two to three sentences that immediately state the tool's purpose, domain, and significance. Every sentence adds value and there is no redundant phrasing.

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 five optional parameters, full schema coverage, and a readOnly annotation, the description provides sufficient high-level context for an agent to understand the tool's focus. It does not describe the return shape, but the absence of an output schema is partially mitigated by the tool's apparent simplicity and the parameters' clear descriptions.

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%, and all five parameters already have clear descriptions in the schema. The description adds contextual framing (doctor/company relationship) but does not add new meaning about parameter syntax or semantics beyond what is already documented.

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 uses a specific verb ('Search') and identifies a distinct resource ('Open Payments OWNERSHIP data') with a clear subject ('doctors with ownership or investment stakes in pharma/device companies'). It clearly differentiates from sibling tools like open_payments_by_physician by focusing specifically on ownership interests.

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 implies when to use this tool: when investigating physician ownership stakes, calling it 'the deepest form of conflict of interest.' However, it does not explicitly mention when not to use it or name alternative sibling tools, so it falls short of full explicit guidance.

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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