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NeuralVerge Business Intelligence

Taiwan company

run_tw_companies

Get one company from the Taiwan registry (MOEA) by 統一編號 or registry link: name, status, registration date, address, company type, capital and shares, representative, business scope, directors, managers, branches, factories, warehouses, stock listing, trademarks and change history. 15 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyYes統一編號 or registry URL. e.g. 22099131

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it usefully discloses a billing trait ('15 point per returned record') plus a broad enumeration of what data is returned. It stops short of stating auth requirements, not-found/error behavior, or any rate limits.

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?

Purpose and identifier formats are front-loaded in the first clause, followed by the returned-field list and pricing. Efficient overall, though the 17-item field enumeration is long and could be trimmed since much of it is inferred from the registry domain.

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?

There is no output schema, so the enumerated return fields (status, capital, directors, branches, trademarks, change history, etc.) usefully compensate for the missing return-value documentation, and the cost note is included. Auth and error semantics are absent but are minor for a simple single-record lookup.

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% and the single parameter is fully documented in the schema ('統一編號 or registry URL. e.g. 22099131'). The description merely restates the same accepted formats, adding no syntax or format detail beyond the schema, so the baseline 3 applies.

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?

States a specific verb ('Get one company') and resource ('Taiwan registry (MOEA)'), including the exact identifier types accepted (統一編號 or registry URL). The singular 'one company' cleanly distinguishes it from the sibling run_tw_companies_search, which handles lookups.

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 phrase 'Get one company ... by 統一編號 or registry link' implies this is a targeted single-record lookup, which implicitly contrasts with the *_search sibling. However, it never explicitly names run_tw_companies_search or states when-not to use this tool, leaving the routing to inference.

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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