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private_officer_search

Find which companies a named person is an officer, director or registered agent of. Use it to check whether a counterparty is who they claim, to map the other entities behind one operator, or to find every company a person controls before signing with any of them. Covers 21.2M officer records.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesOfficer/CEO name or partial name
limitNoMax results (default 25)
stateNoTwo-letter state code, e.g. FL, NY, CA, TX
titleNoFilter by title: ceo, president, director, secretary, treasurer, vp, chairman, manager

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the data coverage ('Covers 21.2M officer records') and the search scope (officer/director/registered agent), but does not mention result shape, pagination, or any limitations beyond the coverage count. This is serviceable but not rich.

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 two sentences plus a coverage count, front-loaded with the primary purpose. Every sentence adds value: purpose, use cases, and data scale. No unnecessary 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?

With 4 parameters and no output schema, the description provides enough context for a search tool: purpose, supported roles, use cases, and data breadth. It doesn't explain return format, but that's not expected when no output schema exists. Lacks only explicit alternative guidance.

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 parameters are already well-documented. The description adds no additional parameter-level detail beyond what the schema provides, which is acceptable and warrants the baseline 3.

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 opens with a specific verb and resource: 'Find which companies a named person is an officer, director or registered agent of.' This clearly differentiates from the sibling private_ceo_search by covering officer/director/agent roles, not just CEO.

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?

It provides concrete usage contexts: 'check whether a counterparty is who they claim', 'map the other entities behind one operator', 'find every company a person controls before signing with any of them.' While it doesn't explicitly state when not to use it or name alternatives, the scenarios are strong enough to guide an agent on when to invoke this tool.

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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TDQS

A4/5.0
Disambiguation5/5

Each tool targets a distinct query type: name search, identity resolution, attribute-based browsing, executive vs officer lookup, entity records, and aggregate statistics. Descriptions explicitly call out when to use one over another (e.g., private_search vs private_resolve vs private_browse).

Naming Consistency5/5

All tool names share the 'private_' prefix and follow snake_case. While some use verbs (browse, search, resolve) and others use nouns (entity, geography, stats), the pattern is highly predictable and the domain is uniformly private company data.

Tool Count5/5

11 tools is right-sized for a business registry server: enough to cover various lookup and analytical needs without redundancy. Each tool has a clear purpose and earns its place.

Completeness5/5

The surface covers the full lifecycle of interacting with company records: discover (search, browse, resolve), detail (entity), people (officer, ceo), signals (owner_operated), aggregations (age, geography, type), and dataset awareness (stats). No obvious gaps for the stated scope.

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