list_company_datasetsFree catalog lookup. Lists the raw regulatory datasets available for one Japanese corporate number with per-call x402 pricing (0.05 USDC per call). Use the dataset tools or the returned api_url to retrieve data.
| Name | Required | Description | Default |
|---|---|---|---|
| corporate_id | Yes | 13-digit Japanese corporate number (法人番号), e.g. 7010001012345 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavioral traits. It mentions pricing (0.05 USDC per call) and that the lookup is free, indicating a read-only, non-destructive action. However, it omits details like authentication requirements, error handling for invalid corporate numbers, rate limits, or the nature of the returned data beyond an api_url.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two sentences that efficiently communicate the tool's nature and usage. The lead phrase 'Free catalog lookup' immediately sets expectations. Each sentence serves a purpose: identifying the action and providing guidance. A minor improvement would be to separate pricing into a note, but overall it is well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with one parameter and no output schema, the description covers the core function, pricing, and next steps. It lacks details about the output structure (e.g., list format, fields) but the reference to api_url partially compensates. Overall, it is adequate for an agent to understand the tool's role in the workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema for corporate_id has 100% coverage and already describes it as a '13-digit Japanese corporate number.' The description merely restates this as 'one Japanese corporate number,' adding no new semantic information about format, constraints, or examples. Baseline of 3 is appropriate given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool 'Lists the raw regulatory datasets available for one Japanese corporate number,' which identifies the specific action and resource. It also calls it a 'catalog lookup,' distinguishing it from data retrieval tools. However, it does not explicitly contrast with sibling tools like get_gazette_financials or search_corporations, missing a clear differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises to 'Use the dataset tools or the returned api_url to retrieve data,' implying the tool is for listing only. It does not specify when to use this tool versus alternatives such as search_corporations or other get_* tools, nor does it mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: searching corporations, listing datasets, retrieving gazette financials, government records, or pension headcount. No overlap in functionality.
All tool names follow a consistent verb_noun pattern in snake_case, using 'get_', 'list_', or 'search_' prefixes. No mixing of conventions.
5 tools is well-scoped for a gateway server providing access to Japanese corporate datasets. Each tool serves a necessary role without redundancy.
The tool surface covers the full workflow: search, catalog, and retrieve three key datasets. Minor gap: no tool for payment status or dataset metadata beyond what list_company_datasets provides.