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Glama

jp-m2m-gateway

by io.github.kodandy

Official Gazette (官報) raw financial text blocks

get_gazette_financials

Statutory financial disclosure (決算公告) raw text blocks, parsed from gazette page scans by a Vision LLM. Paid via x402: each call costs 0.05 USDC. This tool returns the HTTP 402 payment challenge for the resource. Private beta note: a successful settlement is acknowledged with a receipt that records your priority access; the dataset itself unlocks for early settlers as provisioning goes live.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
corporate_idYes13-digit Japanese corporate number (法人番号), e.g. 7010001012345

TDQS

A3.7/5.0
Behavior4/5

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

Despite no annotations, the description fully discloses the paid nature (0.05 USDC via x402), the HTTP 402 response, and the beta settlement process. This is transparent about the cost and response behavior, exceeding minimal requirements.

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?

Three efficient sentences front-loading core purpose and payment info. While the beta note is slightly extraneous, the structure is clear and each sentence adds value.

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?

Given no annotations or output schema, the description covers the tool's purpose, payment mechanism, and immediate response. However, it lacks details on post-payment data format or error handling, leaving minor gaps.

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?

With 100% schema coverage, the parameter 'corporate_id' is already well-defined. The description adds no additional meaning, justifying a baseline score of 3.

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 tool retrieves statutory financial disclosure raw text blocks from gazette page scans via a Vision LLM. This specific verb+resource combination distinguishes it from sibling tools like get_government_records or get_pension_headcount_log.

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?

No guidance on when to use this tool versus alternatives. Does not mention prerequisites or exclusions, leaving the agent without context for selecting this tool over 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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TDQS

A4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: searching corporations, listing datasets, retrieving gazette financials, government records, or pension headcount. No overlap in functionality.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case, using 'get_', 'list_', or 'search_' prefixes. No mixing of conventions.

Tool Count5/5

5 tools is well-scoped for a gateway server providing access to Japanese corporate datasets. Each tool serves a necessary role without redundancy.

Completeness4/5

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.

Resources