SupplyGraph.AI

Search Region Candidates

search_region_candidates

Resolves natural-language country or region names (including aliases and abbreviations) against SupplyGraph’s internal geography registry and returns a list of standardized region names for downstream agent and MCP tool consumption.

Pricing: {"unit": "credits", "billing_model": "per_run", "per_run": 1}

Input Schema

TableJSON Schema

Name	Required	Description	Default
`text`	Yes	Country or region name in natural language, including aliases and abbreviations (e.g. 'China', 'USA', 'South Korea', 'Hong Kong', '中国', '美国'). The tool searches the internal geography registry and returns standardized matching region names for caller-side selection.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A3.9/5.0

Behavior3/5

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

The openWorldHint annotation is present, indicating non-exhaustive results. The description adds that the tool returns a list and consumes natural language with aliases, but does not disclose additional behavioral aspects like pagination, error behavior, or rate limits. No contradiction with annotations.

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 two sentences, with the purpose front-loaded and no redundant information. The pricing detail is concise and useful. Every word earns its place.

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?

The tool is simple with one parameter, an output schema exists, and the openWorldHint annotation covers the open-world nature. The description sufficiently conveys the tool's function and output for downstream use. No critical information appears missing.

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?

The input schema has 100% coverage with a detailed description of the 'text' parameter including examples and behavior. The description repeats the core functionality but does not add any new semantic information beyond what the schema already provides. Baseline 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 clearly states the verb 'resolves' against 'SupplyGraph's internal geography registry' and specifies the output as 'standardized region names'. It distinguishes from sibling search_company_candidates by focusing on regions rather than companies.

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 context is implied through the description (for resolving natural-language region names), but there is no explicit guidance on when to use this tool versus alternatives, nor any exclusion criteria. It relies on the agent to infer the appropriate context.

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

B3.1/5.0

Disambiguation3/5

Most tools are clearly distinct (e.g., tariff_calc vs. tariff_classification, search_* vs. sg_*). However, corporate_exception_report and due_diligence_report both produce company reports with overlapping chapter lists and vague descriptions, creating potential confusion for an agent selecting the appropriate report.

Naming Consistency2/5

Naming conventions are mixed: search_company_candidates and search_region_candidates follow verb_noun, but others use noun phrases (tariff_calc, due_diligence_report) and some use an 'sg_' prefix (sg_chokepoint, sg_visualization). This lack of a consistent pattern reduces predictability.

Tool Count5/5

With 9 tools, the count is well within the ideal 3-15 range and matches the platform's scope—company search, due diligence, supply chain analysis, and tariff handling. Each tool serves a clear purpose without unnecessary bloat.

Completeness4/5

The surface covers core workflows: company identification (search), deep reporting (due diligence, exception report), supply chain analysis (chokepoint, visualization, risk prediction), and tariff handling (classification, calculation). Minor gaps exist, such as a dedicated tool for fetching a specific company profile, but due_diligence_report largely fills that need.

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