GlobalEntity API

Find decision makers in Norwegian companies

find_decision_makers

Read-onlyIdempotent

Find people by role — daglig leder (CEO / managing director), styreleder (chair), styremedlem (board member), innehaver (owner of a sole proprietorship), deltaker (partner) — in Norwegian companies matching filters such as county, municipality, industry (NACE), employees, revenue and revenue growth. Returns the person's name and role, the company (org. number, size, revenue, growth) and a LinkedIn people-search link. Names and roles come from the public Register of Business Enterprises; no personal e-mail or phone numbers are provided. At least one company filter is required; max 50 people per call.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "find_decision_makers"
  }
}

Input Schema

Name	Required	Description
`limit`	No	Maximum people (default 20, max 50).
`roles`	No	Comma-separated roles: daglig leder / CEO, styreleder / chair, nestleder, styremedlem / board member, innehaver / owner, deltaker / partner. Default: daglig leder.
`county`	No	Norwegian county (fylke) name or number, e.g. Akershus, Oslo, Vestland.
`offset`	No	Skip this many results (paging).
`org_number`	No	Restrict to one company (9-digit org. number).
`company_name`	No	Part of the company name.
`municipality`	No	Municipality (kommune) name or 4-digit number.
`employees_max`	No	Maximum employees of the company.
`employees_min`	No	Minimum employees of the company.
`industry_nace`	No	NACE code or prefix, e.g. 62, 43.2, 69.2.
`revenue_min_nok`	No	Minimum company revenue in NOK.
`revenue_growth_min_pct`	No	Minimum company revenue growth vs the previous year in %.

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 26, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already cover read-only/idempotent/open-world, and the description adds genuinely new context: the data source (public Register of Business Enterprises), the explicit privacy boundary (no personal e-mail or phone numbers), and the 50-person cap. It doesn't discuss paging behavior beyond the offset default, so not a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with the purpose and role list, then return shape, then constraints. The role parenthetical is long but functional since it maps Norwegian titles to agent-understandable roles; little else could be cut without losing signal.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description carries the return-value burden and does so concretely (person name/role, company org. number, size, revenue, growth, LinkedIn search link). Combined with the source and privacy notes, an agent has everything needed to call and interpret it.

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 coverage is 100%, so the schema already documents every parameter including the role vocabulary and NACE/county formats. The description restates the role glosses and filter categories but adds no format, default, or interaction semantics beyond the schema, making baseline 3 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?

Opens with a specific verb+resource ('Find people by role ... in Norwegian companies') and enumerates the exact role vocabulary, so an agent can immediately tell this returns persons rather than companies, which is the key distinction from siblings like find_companies and search_companies.

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?

Gives a hard precondition ('At least one company filter is required') and a per-call cap (max 50), which are real usage constraints. It does not explicitly name an alternative tool or state when to prefer find_companies over this one, so it stays short of a 5.

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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