mcp-revenue-empire — Japan public-data ledgers

temporal_query

Reconstruct what a ledger item (or items matching a query) officially said AS OF a past date T, by replaying the kept event history. Returns each item's point-in-time state plus an F-037 provenance receipt (observed_at = the state's effective time). existence:false with a first_seen receipt when the item did not yet exist at T; latest state with as_of_clamped:false when T is in the future. Read-only; price 0.0.

Input Schema

TableJSON Schema

Name	Required	Description
`as_of`	Yes	ISO-8601 point in time T.
`query`	No	Title substring to reconstruct every matching item (capped at 25). Use instead of item_id.
`ledger`	Yes	Ledger key (e.g. 'sanction', 'license', 'subsidy', 'recall', 'pharma', 'bid', 'grant', 'pubcom', 'ordinance', 'tos', 'realestate', 'landprice').
`item_id`	No	Stable item id (single-item reconstruction).
`jurisdiction`	No	Jurisdiction code (default 'jp').

TDQS

A4.7/5.0

Behavior5/5

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

With no annotations, the description fully covers behavioral traits: read-only, price 0.0, return format including provenance receipt, handling of future dates (as_of_clamped:false) and non-existence (existence:false). No contradictions.

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 concise (3-4 sentences) and front-loaded with the main purpose. Every sentence adds necessary detail without waste.

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?

No output schema, so description must explain return values. It clearly describes the state, receipt, and edge cases. This makes it complete for an agent to understand tool behavior.

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% so baseline is 3. The description adds value by explaining capping on query results (25), interaction between query and item_id, and the effect of as_of on receipts. This extra context justifies 4.

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 reconstructs the state of ledger items at a past date, using specific verbs like 'reconstruct' and 'replay'. It distinguishes itself from siblings (no other temporal query tool) and is specific about the resource (ledger items) and action (point-in-time reconstruction).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use the tool (for historical reconstruction) and includes edge cases (future T, non-existence). While it doesn't explicitly exclude other tools, the unique functionality of temporal query makes alternatives unnecessary in 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

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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