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mcp-revenue-empire — Japan public-data ledgers

sanctions_screen_entity

Screen an entity name against public consolidated sanctions lists (OFAC SDN / UN / EU), fetched at request time. Returns scored fuzzy matches with programs and countries. Informational only, not legal advice. Read-only; price 0.0 (free).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesEntity / person / vessel name to screen
limitNoMax matches to return
typesNoRestrict to sanction subject types.
minScoreNoMinimum match score 0-100 (default heuristic threshold)

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries full burden. It confirms the tool is read-only, free, and fetches data at request time. However, it does not disclose potential side effects (e.g., rate limits, caching behavior), the return format structure, or error handling for invalid inputs.

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 compact (four sentences) and front-loaded with the core purpose. Every sentence adds value: screening action, data sources, output type, disclaimers, pricing. No wasted words.

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 output schema, the description covers return format ('scored fuzzy matches with programs and countries') and data freshness. It lacks detail on the structure of individual matches, which might be inferred from parameter semantics. Overall, sufficient for a straightforward screening tool.

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 descriptions for all four parameters. The description adds minimal extra value beyond the schema—e.g., it notes 'scored fuzzy matches' but does not explain how minScore interacts with that scoring. 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 uses a specific verb ('Screen') and resource ('entity name against public consolidated sanctions lists'), clearly distinguishing from siblings like sanctions_screen_by_country or sanctions_screen_check_address. It also mentions the output type ('scored fuzzy matches').

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?

The description states the tool is 'read-only' and 'informational only, not legal advice,' but does not explicitly guide when to use this tool vs. other sanctions-related tools (e.g., sanctions_screen_by_country, list_programs). Usage context is implied but no alternative tools are mentioned.

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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