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Glama

Company Intel

by com.timzinin.api

Taiwan Company KYB Lookup

taiwan-company-kyb-lookup

Resolve Taiwan companies (統一編號 or legal name) to an evidence-backed KYB card from the official MOEA GCIS open-data registry. Free structural checks, free not-found/ambiguous/error outcomes; billed only for a complete, unambiguous company card. — $0.01/call, x402 (USDC on base).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companiesYesOne to 100 companies. Give either unifiedBusinessNumber or legalNameZhTw for each entry, never both.
includeBoardNoWhether to also fetch the company's board of directors/supervisors and shareholding from the registry. This is personal-data-bearing: names and shareholding of living people. Turn off to request only the company card. Default: true.
maxConcurrencyNoCompanies processed concurrently only in local non-monetized runs. On-platform source work and paid delivery are sequential regardless of this value, and every request to the registry is paced conservatively either way.

TDQS

A4.2/5.0
Behavior4/5

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

The description discloses the monetary side effect (billed only for complete unambiguous results) and the free outcomes, which is behavioral context beyond the sparse annotations. It also names the official keyless open-data source. No contradiction with annotations; the readOnlyHint=false is consistent with the charging behavior.

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 composed of two concise sentences and a price tag, each carrying necessary information: purpose, source, billing conditions, and cost. No fluff or redundancy; fully front-loaded.

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?

The description covers purpose, data source, and commercial terms, while the schema thoroughly documents all parameters. However, there is no output schema and the description does not detail what an 'evidence-backed KYB card' contains, leaving a minor gap in expected return semantics. Still sufficient for its narrow scope.

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% with rich descriptions for each parameter (Unified Business Number pattern, legal-name length, includeBoard default, maxConcurrency behavior). The description only mentions the two identifiers at a high level, adding no additional semantics beyond the schema, so the baseline score of 3 is 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?

The description opens with a specific verb ('Resolve') and an explicit resource ('Taiwan companies') using either identifier (統一編號 or legal name), clearly producing an 'evidence-backed KYB card' from a named official registry. This distinguishes it from sibling tools like generic 'company-lookup' by being Taiwan-specific and KYB-focused.

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?

The description sets clear context for Taiwan-company KYB lookup via the MOEA GCIS registry and explains when billing applies (free for structural checks, not-found/ambiguous/error; billed only for a complete card). It does not explicitly name alternatives or exclusions, but the niche is well defined.

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

A3.8/5.0
Disambiguation3/5

Several tools overlap in signal space: hiring-radar, hiring-trend-index, layoff-tracker, and intent-signal-aggregator all touch hiring; funding-alert vs funding-round-tracker, sanctions-screening vs sanctions-update-alert, and rollup tools vs individual checks create boundary ambiguity. However, each has a distinct output format, so descriptions help.

Naming Consistency4/5

Tool names are consistently lowercase with hyphens and descriptive noun phrases (e.g., company-hiring-radar, litigation-check), but pricing_info breaks the pattern with snake_case and a non-descriptive name.

Tool Count3/5

With 20 tools, the server feels heavy and covers a wide range of premium data services, but each tool does target a distinct data source or workflow, so it's borderline rather than excessive.

Completeness4/5

The surface covers company identity, hiring, litigation, sanctions, funding, and patents well, but lacks direct financials, ownership structure, and general news monitoring beyond funding/layoffs, leaving some sales-intelligence gaps.

Resources