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Japan Restaurant Calories

List covered chains

list_chains
Read-onlyIdempotent

List the restaurant chains covered, with item counts, which nutrients each chain publishes, the source document and when it was fetched. query filters by chain name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description usefully adds the return payload (item counts, nutrient coverage, provenance/refresh metadata), but says nothing about pagination, result size, or ordering, which is the main remaining behavioral gap.

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?

A single dense sentence that front-loads the resource and then itemizes the return fields, with the parameter note appended efficiently. No filler, though the field list runs long enough that a second short sentence for usage would have been worth the space.

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?

For a read-only list tool with full annotation coverage and no output schema, the description carries the return-value burden well by naming the columns returned. Pagination behavior and match semantics for 'query' are the only things an agent would still need to guess at.

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 0% and the single parameter is generically named 'query', so the description's 'query filters by chain name' is genuinely additive — it disambiguates the opaque parameter name by naming the target field and matching semantics (partial vs exact is still unclear). It adds real meaning beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('List the restaurant chains covered') and enumerates the returned fields (item counts, published nutrients, source document, fetch time), so the agent knows exactly what this tool yields. It does not explicitly contrast itself with siblings like search_menu, so it stops short of a 5.

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

Usage Guidelines2/5

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

The only usage hint is 'query filters by chain name', which describes an input rather than when to choose this tool over search_menu or sum_items. No conditions, prerequisites, or alternatives are given, leaving selection entirely to inference.

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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