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get_ramen_shop

Read-onlyIdempotent

Fetch one ramen shop by its stable id (rk_000001 style) — full record incl. address, coordinates, ramen style (keito), nearest station (Japan Station Master st_xxxx id + distance), tri-state payment facts, and the freshness block (first_seen/last_seen/status/closure evidence URL). No id? Pass name + pref instead and the best match is returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoStable shop id, e.g. rk_000851. Preferred.
cityNoMunicipality (e.g. 松戸市) — alternative to pref; prefecture auto-resolved.
nameNoShop name (Japanese) — used with pref or city when id is unknown.
prefNoPrefecture (千葉県; short form 千葉 also OK) — pref or city required with name.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
shopNo
errorNoSet when the shop was not found.
data_as_ofNoDataset freshness date.
attributionNoData source(s), license and provenance — an object, or an array of sources.
definitionsNoField definitions (or a note string in the no-auth preview).

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds behavioral context beyond that: the 'best match' behavior when no id is supplied, and the fact that the full record contains specific fields including coordinates, station info, payment facts, and freshness block. No contradictions with annotations.

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?

A single dense sentence that front-loads the primary usage (fetch by id), then offers the alternative path, and lists the record contents efficiently. Every phrase earns its place, with no filler or redundancy.

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?

Given an output schema exists, the description does not need to explain return fields. The tool is a simple single-shop fetch with moderate complexity. The description covers both invocation paths and hints at the richness of the record. Annotations cover safety, and the schema covers parameters. Nothing essential is missing for an agent to call this correctly.

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 input schema covers all four parameters with descriptions, so coverage is 100% (baseline 3). The description adds value by signaling that 'id' is the preferred parameter and that name+pref (or city) are used as a fallback. It also clarifies the relationship between name and location parameters, which the schema does not explicitly connect.

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 verb 'Fetch' and the resource 'one ramen shop' with a stable id. It also explains the alternative lookup by name+pref, and the explicit list of fields distinguishes it from sibling tools like search_ramen or get_ramen_changes.

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 provides clear guidance on when to use the id parameter versus the name+pref alternative: 'No id? Pass name + pref instead'. It implies this tool is for fetching a single specific shop, but does not explicitly exclude scenarios where search_ramen would be more appropriate. The context is clear enough for an agent to decide.

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

A4.7/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: ping for health, get_ramen_shop for single-record fetch, search_ramen for exact/filtered queries, vibe_search for semantic/fuzzy queries, and get_ramen_changes for the data freshness feed. The overlap between search_ramen and vibe_search is explicitly addressed in their descriptions, eliminating ambiguity.

Naming Consistency4/5

Tool names follow a consistent verb_noun pattern in snake_case (get_ramen_changes, get_ramen_shop, search_ramen, vibe_search), with ping being the only exception as a bare verb health check. This is a minor deviation but still readable and predictable.

Tool Count5/5

With 5 tools, the server is well-scoped for a read-only database/search service. Each tool covers a necessary operation without redundancy, and the count is neither thin nor bloated.

Completeness5/5

The server provides full retrieval coverage: single-record retrieval, exact search, semantic search, and a change feed for data freshness. As a read-only service, it does not need create/update/delete operations, and the existing surface covers all plausible agent needs for querying ramen shop data.

Resources