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Asian Recs

Search Asian Recs

search_places
Read-onlyIdempotent

Find places in San Francisco or New York ranked by how Asian diners rate them. Each result has the Asian diners' rating, everyone else's rating, the gap between them, how many Asian diners reviewed it, top dishes, neighborhood and a link to its page.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYessf = San Francisco, nyc = New York
nearNoA point to measure distance from; adds distance_mi to results.
sortNoasian_rating: Asian diners' rating, highest first; loved_more: Biggest gap above everyone else; most_asian_diners: Most Asian diners; share_asian: Highest share of Asian reviewers; distance: Closest first (needs near). Default asian_rating.
typeNoKind of place. Default restaurants.
limitNoDefault 10.
queryNoFree text matched against name, cuisine, neighborhood and dishes, e.g. a dish like "soup dumplings".
cuisineNoCuisine or drink category, e.g. "ramen", "sichuan", "korean", "boba", "dim sum".
locationNoNeighborhood or area, e.g. "Mission", "East Village", "Flushing", "Manhattan — Downtown".
radius_miNoWith near: only places within this many miles.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare this as a safe, idempotent, closed-world read. With no output schema, the description earns real credit by enumerating the returned fields (both ratings, the gap, diner counts, top dishes, neighborhood, link), which tells the agent what it gets back. It stops short of disclosing result caps, default limit behavior, or pagination.

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?

Two sentences, front-loaded with purpose and scoping, then the result shape. Every clause carries information, and the second sentence compensates for the absent output schema rather than padding.

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 9-parameter search with a nested object, three enums, and no output schema, the description covers the core intent and the return shape well. It omits operational details an agent might want (default/max result counts, how filters combine, ordering defaults), but the schema picks up most of that slack.

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% and every one of the 9 parameters (including the nested near object and all three enums) is documented in the schema itself. The description adds no syntax, format, or interaction guidance beyond restating the SF/NY scope, so the baseline 3 applies.

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?

Opens with a specific verb and resource ('Find places') and immediately scopes it to two named cities ranked by a named criterion (how Asian diners rate them). This is clearly distinct from the sibling get_place (a detail lookup) and list_filters (enumerating filter vocabularies), so an agent can route between them without opening a schema.

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

Usage Guidelines3/5

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

Usage is implied by the framing ('Find places ... ranked by how Asian diners rate them'), which conveys the discovery use case, but there is no explicit when-to-use vs get_place, no mention of when a query/cuisine/location combination is appropriate, and no exclusions. Adequate but leaves the agent to infer routing.

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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