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NeuralVerge Business Intelligence

Sweden companies search

run_se_companies_search

Search the Sweden company registry (Bolagsverket) by company name or organisation number: name, organisation number, status, city, legal form and card link. 1 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNoStatus. Options: active = Active, inactive = Inactive / dissolved
keywordYesCompany name. e.g. volvo
max_itemsNoMax items (up to 250) Default: 25.
start_pageNoStarting page

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior3/5

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

No annotations exist, so the description carries the behavioral burden. It does disclose two useful traits: the returned field set and the pricing model ('1 point per returned record'), which directly informs how the agent should set max_items. However, it says nothing about rate limits, pagination semantics, or what happens for non-matching queries.

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?

A single front-loaded sentence covers purpose, source, inputs, outputs and cost with no filler. The trailing field list reads as a slightly abrupt clause and the returned-field enumeration is doing double duty, but nothing is wasted.

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 no output schema and no annotations, the description compensates by naming the returned fields and the point cost, and the four parameters are fully documented in the schema. The only gap is the absence of any guidance tying start_page/max_items to pagination behavior and cost budgeting, which the agent must infer.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds genuine meaning: the schema describes 'keyword' only as 'Company name. e.g. volvo', whereas the description clarifies that an organisation number is also accepted. That is a real semantic addition over the structured field.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource ('Search the Sweden company registry (Bolagsverket)') and lists the retrieved fields, so an agent knows exactly what the tool produces. It distinguishes itself from the sibling run_se_companies (which returns a single company card) implicitly via 'search', but never names the alternative explicitly.

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?

Usage is only implied: 'by company name or organisation number' tells the agent what input shape to supply, but there is no explicit when-to-use statement and no mention of the sibling run_se_companies or run_se_company_filings as alternatives for detail or filing lookups. Adequate but requires inference from the sibling names.

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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