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guide_consensus

Read-only

Rank restaurants by how many distinct guides feature them, optionally filtered by theme. Use for 'where can't I go wrong' or safest-bet picks. Differs from find_guides: this returns ranked restaurants, not the guides themselves. Each row carries guide_appearance_count (a number); get_restaurant's guide_appearances is the full entry list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYesCity slug, always required. Currently 'new-york', covering the five boroughs plus the immediate metro (within 30 km of Manhattan).
limitNoMax results (default 10)
themeNoGuide theme, e.g. 'ramen', 'brunch'

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / city / description
      Previous value: -"City slug, always required. Currently 'new-york'."New value: +"City slug, always required. Currently 'new-york', covering the five boroughs plus the immediate metro (within 30 km of Manhattan)."
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds behavioral context beyond this: ranking by distinct guide count, returning guide_appearance_count as a numeric field, and clarifying that get_restaurant's guide_appearances is a different, fuller representation. This is useful for setting expectations about the result shape.

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?

Four sentences, each earning its place: the core action, the intended use case, the key sibling distinction, and a clarifying note about the return field. It is front-loaded with the ranking purpose and wastes no 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?

There is no output schema, but the description covers the key return-field behavior (guide_appearance_count) and sets expectations for what the results are. It also addresses the most relevant sibling relationship. Minor gaps like pagination or exact ordering details are not critical given the schema covers parameters and the annotations cover read-only safety.

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 description coverage is 100%, so the schema already explains all three parameters. The description's mention of 'optionally filtered by theme' reinforces the theme parameter but does not materially add meaning beyond the schema. Baseline 3 is appropriate because the schema carries the parameter documentation load.

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 states a specific verb and resource: 'Rank restaurants by how many distinct guides feature them'. It also explicitly distinguishes itself from find_guides by noting this returns ranked restaurants rather than the guides themselves, so an agent can differentiate it without opening the schema.

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

Usage Guidelines5/5

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

It gives a clear when-to-use signal: 'Use for where can't I go wrong or safest-bet picks'. It also names the closest alternative (find_guides) and explains the difference, giving the agent both positive and negative routing guidance.

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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