mcp-revenue-empire — Japan public-data ledgers

freshness_subscribe

Subscribe a machine/AI pipeline to ledger-change notifications: when a matching record changes, a signed "stale" event (with an F-037 receipt proving the change) is POSTed to your callback_url so your RAG/index can re-index. Filters: ledger (optional), entity and/or topic (case-insensitive title substring). At least one filter is required. Body is HMAC-signed with your secret (X-Receipt-Signature). Backfill never fires. Price 0.0.

Input Schema

TableJSON Schema

Name	Required	Description
`topic`	No	Additional case-insensitive substring
`entity`	No	Case-insensitive substring of the item title
`ledger`	No	Ledger key, e.g. 'sanction' (omit for all ledgers)
`secret`	Yes	Shared secret used to HMAC-sign the POST body
`callbackUrl`	Yes	HTTPS endpoint the stale event is POSTed to
`jurisdiction`	No	Jurisdiction code (default 'jp')

TDQS

A4.4/5.0

Behavior4/5

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

Without annotations, the description details the signed POST event, HMAC signing, filter behavior, and constraints (no backfill). It provides sufficient transparency for a subscription tool.

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?

The description is concise and front-loaded with purpose. It packs many details into a single paragraph, but may benefit from bullet points for clarity. Still, every sentence adds value.

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?

For a tool with no output schema and no annotations, the description is comprehensive: covers trigger, security, filters, and cost. No significant gaps identified.

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?

The description adds meaning beyond the schema: explains filter behavior (case-insensitive substring), that at least one filter is required, and the purpose of the secret. It does not elaborate on the jurisdiction default.

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 subscribes a pipeline to ledger-change notifications for re-indexing, using a specific verb and resource. It distinguishes from siblings 'freshness_list' and 'freshness_unsubscribe' by focusing on subscription creation.

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?

It explains when to use the tool (when a matching record changes) and specifies required filters. It mentions backfill never fires and price 0.0, but lacks explicit exclusions or direct comparisons to alternatives like polling.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All mcp-revenue-empire — Japan public-data ledgers tools Inspect

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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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