mcp-revenue-empire — Japan public-data ledgers

kyb_report

Turn a company/entity name into a structured English KYB / due-diligence report for foreign-inbound buyers. Aggregates cross-ledger hits (administrative sanctions, licenses, public bids, recalls, etc.) via entity_search, summarizes them (counts + deterministic risk_flags), and attaches an F-037 provenance receipt to EACH hit so the screening is auditable. No model-invented facts: every asserted fact originates from a ledger hit and carries a receipt. Informational only; not legal advice. Price 0.0.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`query`	Yes	Company / entity name (partial match across all ledgers)
`jurisdiction`	No	Jurisdiction code (default 'jp')

TDQS

A4.4/5.0

Behavior5/5

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

With no annotations, description fully discloses behavior: it aggregates cross-ledger hits via entity_search, summarizes with counts and risk_flags, attaches F-037 provenance receipts, and asserts no invented facts. This provides comprehensive transparency beyond basic purpose.

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?

Description is front-loaded with the core purpose and efficiently conveys key details. While slightly verbose, each sentence adds value (aggregation method, risk flags, receipts, disclaimers). Structure is logical and easy to parse.

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?

Despite no output schema, description clearly explains the output structure: a structured English report with aggregated hits, counts, risk_flags, and provenance receipts. It also covers input constraints (partial match) and limitations (no invented facts), making it complete for a report-generation tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% (both parameters documented). Description adds value by clarifying that 'query' supports partial matching across all ledgers and that 'jurisdiction' has a default of 'jp', which goes beyond the schema definitions.

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?

Description clearly states the tool converts a company/entity name into a structured English KYB/due-diligence report for foreign-inbound buyers. It specifies the verb 'turn into,' the resource (report), and the context (foreign-inbound buyers), distinguishing it from lower-level search tools like entity_search.

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?

Description provides context (for foreign-inbound buyers) and includes a disclaimer that it's informational only, but does not explicitly state when not to use this tool or mention alternative tools. It implies usage for due-diligence screening but lacks exclusionary guidance.

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

Disambiguation4/5

Most tools are clearly distinguished by domain prefixes (e.g., bid_watch, grant_watch) and specific action verbs. However, the high number of similarly structured watch tools could still cause confusion, though descriptions clarify exact purposes.

Naming Consistency5/5

Every tool follows a consistent `domain_subdomain_action` pattern with underscores, e.g., `agent_audit_query`, `bid_watch_search`. Even long names like `commerce_catalog_agent_readiness_score` adhere to this structure.

Tool Count2/5

With 147 tools, the server is far too broad, covering weather, carbon estimates, domain intel, and more—well beyond its stated 'Japan public-data ledgers' scope. This sheer volume overwhelms agents and dilutes focus.

Completeness3/5

The server offers many read-only tools for Japanese public data (bids, grants, licenses, etc.), but lacks create/update/delete operations for those domains. Additionally, numerous unrelated tools (e.g., carbon estimates, weather) feel tacked on, leaving gaps in core coverage.

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