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lzinga

US Government Open Data MCP

open_payments_ownership

Search financial ownership data to identify doctors with investment stakes in pharmaceutical or medical device companies, revealing potential conflicts of interest in prescribing practices.

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
companyNoCompany name: 'Pfizer', 'Johnson & Johnson'
doctorNoDoctor last name
stateNoTwo-letter state: 'CA', 'WA'
yearNoYear (auto-discovers latest if omitted)
limitNoMax results (default 20)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions the data type and conflict-of-interest context, it doesn't describe key behavioral traits such as whether this is a read-only operation, what the output format looks like, whether there are rate limits, authentication requirements, or any side effects. The description is insufficient for a tool with no annotation coverage.

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 efficiently structured in two sentences. The first sentence directly states the tool's purpose, and the second adds important context about conflict of interest. There's no wasted text, and key information is front-loaded appropriately.

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?

Given the complexity of searching ownership data with 5 parameters, no annotations, and no output schema, the description is incomplete. It lacks information about what the tool returns, how results are structured, any limitations or constraints, and behavioral context. The description doesn't compensate for the missing structured data that would help an agent use this tool effectively.

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 the schema already documents all 5 parameters with clear descriptions. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain relationships between parameters or provide usage examples). With high schema coverage, the baseline score 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 with specific verbs ('Search Open Payments OWNERSHIP data') and identifies the resource ('doctors with ownership or investment stakes in pharma/device companies'). It distinguishes this from sibling tools by specifying it deals with 'ownership' data, unlike other open_payments tools that focus on different aspects like 'by_company' or 'by_physician'.

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 context by stating this is 'The deepest form of conflict of interest' and shows 'which doctors have financial interests in the companies whose products they prescribe.' However, it doesn't explicitly state when to use this tool versus alternatives (like other open_payments tools), nor does it provide any exclusion criteria or prerequisites for usage.

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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