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NeuralVerge Business Intelligence

Canada companies search

run_ca_companies_search

Search federal corporations in the Corporations Canada registry by name, corporation number or business number: name, corporation number, status, business number and link. 1 point per returned record.

Input Schema

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

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.4/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It usefully discloses the cost model ('1 point per returned record'), a genuine behavioral trait, but says nothing about pagination semantics, result caps, rate limits, or auth. It is a read-only search by implication only.

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 sentence with the core purpose front-loaded, followed by the field list and cost note. The colon-joined field enumeration is slightly dense 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, the description compensates by listing returned fields (name, corporation number, status, business number, link) and disclosing the cost. It omits pagination and rate-limit behavior for a 4-parameter paged search, which keeps it short of complete.

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 meaning by stating the keyword can match corporation number or business number in addition to name — information the schema's keyword field ('Corporation name') omits. This is a slight tension with the schema but is net value-adding.

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 names a specific verb (Search) and resource (federal corporations in the Corporations Canada registry) and enumerates the search keys and returned fields, so the agent knows exactly what it does. It does not, however, explicitly differentiate from the sibling run_ca_companies (the non-search counterpart), leaving that distinction to inference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use or when-not-to-use guidance and no alternative is named. The agent must infer from 'Search' that this is the lookup tool versus run_ca_companies, and gets no help choosing between the many country-specific search siblings.

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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