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Seemor Restaurant Intelligence

Explore Area

explore_area
Read-onlyIdempotent

Get aggregate dining statistics for a neighborhood, city, or region: cuisine breakdown, grade distribution, price range, top neighborhoods, and highlighted restaurants. Use this for area-level context ("what is the dining scene like in Shoreditch?"), NOT for finding a specific restaurant or getting a personal recommendation. For "find me a quiet Italian near Shoreditch", use the recommend tool instead. Coverage is reported honestly: coverage_level 'full' (fully analyzed rows present), 'basic' (only quick-read rows: review-analysis bands, no letter grades yet), or 'none'; analyzed_count and preliminary_count split total_restaurants, and highlights marked coverage_level 'basic' carry a preliminary_band instead of a grade. not_found means neither analyzed nor preliminary rows exist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
areaYesNeighborhood, city, or region name, in English or the local language. Supports 'Shoreditch', 'Shoreditch, London', 'Rome' or 'Roma', 'Wien', 'Praha', 'Montréal', 'Chelsea, NYC'. Whenever the conversation shows which place is meant, add its city, state or country after a comma, so a shared name needs no guess; other_places lists the others when a name is shared.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
areaNo
statusNo
messageNo
highlightsNo
place_noteNo
descriptionNo
other_placesNo
top_cuisinesNo
neighborhoodsNo
analyzed_countNo
coverage_levelNo
price_breakdownNo
preliminary_countNo
total_restaurantsNo
grade_distributionNo
analyzed_restaurantsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedOutput schema / properties / highlights / items / properties / place_note
      Added value: +{
      +  "type": [
      +    "string",
      +    "null"
      +  ]
      +}
  2. Changed1 schema field changed
    • changedInput schema / properties / area / description
      Previous value: -"Neighborhood, city, or region name, in English or the local language. Supports 'Shoreditch', 'Shoreditch, London', 'Rome' or 'Roma', 'Wien', 'Praha', 'Montréal', 'Chelsea, NYC'. Use a comma qualifier to pick between places that share a name; other_places lists them when a name is shared."New value: +"Neighborhood, city, or region name, in English or the local language. Supports 'Shoreditch', 'Shoreditch, London', 'Rome' or 'Roma', 'Wien', 'Praha', 'Montréal', 'Chelsea, NYC'. Whenever the conversation shows which place is meant, add its city, state or country after a comma, so a shared name needs no guess; other_places lists the others when a name is shared."
  3. Changed3 schema fields changed
    • changedInput schema / properties / area / description
      Previous value: -"Neighborhood, city, or region name. Supports 'Shoreditch', 'Shoreditch, London', 'Central London', 'Rome', 'Chelsea, NYC'. Use comma to disambiguate neighborhoods that exist in multiple cities."New value: +"Neighborhood, city, or region name, in English or the local language. Supports 'Shoreditch', 'Shoreditch, London', 'Rome' or 'Roma', 'Wien', 'Praha', 'Montréal', 'Chelsea, NYC'. Use a comma qualifier to pick between places that share a name; other_places lists them when a name is shared."
    • addedOutput schema / properties / other_places
      Added value: +{
      +  "items": {
      +    "type": "object"
      +  },
      +  "type": "array"
      +}
    • addedOutput schema / properties / place_note
      Added value: +{
      +  "type": "string"
      +}
  4. Changed1 schema field changed
    • changedOutput schema / properties / highlights / items / properties / coverage_level / enum
      Previous value: -[
      -  "full",
      -  "basic"
      -]New value: +[
      +  "full",
      +  "basic",
      +  "none"
      +]
  5. Changed6 schema fields changed
    • addedOutput schema / properties / analyzed_count
      Added value: +{
      +  "type": "number"
      +}
    • addedOutput schema / properties / coverage_level
      Added value: +{
      +  "enum": [
      +    "full",
      +    "basic",
      +    "none"
      +  ],
      +  "type": "string"
      +}
    • changedOutput schema / properties / description / type
      Previous value: -"string"New value: +[
      +  "string",
      +  "null"
      +]
    • addedOutput schema / properties / highlights / items / properties
      Added value: +{
      +  "address": {
      +    "type": [
      +      "string",
      +      "null"
      +    ]
      +  },
      +  "caveats": {
      +    "items": {
      +      "type": "string"
      +    },
      +    "type": "array"
      +  },
      +  "city": {
      +    "type": [
      +      "string",
      +      "null"
      +    ]
      +  },
      +  "coverage_level": {
      +    "enum": [
      +      "full",
      +      "basic"
      +    ],
      +    "type": "string"
      +  },
      +  "cuisine_tags": {
      +    "items": {
      +      "type": "string"
      +    },
      +    "type": "array"
      +  },
      +  "distance_km": {
      +    "type": [
      +      "number",
      +      "null"
      +    ]
      +  },
      +  "grade": {
      +    "type": [
      +      "string",
      +      "null"
      +    ]
      +  },
      +  "name": {
      +    "type": "string"
      +  },
      +  "neighborhood": {
      +    "type": [
      +      "string",
      +      "null"
      +    ]
      +  },
      +  "preliminary_band": {
      +    "type": [
      +      "string",
      +      "null"
      +    ]
      +  },
      +  "price_level": {
      +    "type": [
      +      "string",
      +      "null"
      +    ]
      +  },
      +  "seemor_id": {
      +    "type": "string"
      +  },
      +  "tldr": {
      +    "type": [
      +      "string",
      +      "null"
      +    ]
      +  }
      +}
    • addedOutput schema / properties / preliminary_count
      Added value: +{
      +  "type": [
      +    "number",
      +    "null"
      +  ]
      +}
    • addedOutput schema / properties / status / enum
      Added value: +[
      +  "ok",
      +  "error",
      +  "not_found"
      +]
  6. Changed4 schema fields changed
    • addedOutput schema / properties / description
      Added value: +{
      +  "type": "string"
      +}
    • addedOutput schema / properties / message
      Added value: +{
      +  "type": "string"
      +}
    • addedOutput schema / properties / neighborhoods
      Added value: +{
      +  "items": {
      +    "type": "object"
      +  },
      +  "type": "array"
      +}
    • addedOutput schema / properties / price_breakdown
      Added value: +{
      +  "type": "object"
      +}
  7. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "properties": {
      +    "analyzed_restaurants": {
      +      "type": "number"
      +    },
      +    "area": {
      +      "type": "string"
      +    },
      +    "grade_distribution": {
      +      "type": "object"
      +    },
      +    "highlights": {
      +      "items": {
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "status": {
      +      "type": "string"
      +    },
      +    "top_cuisines": {
      +      "items": {
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "total_restaurants": {
      +      "type": "number"
      +    }
      +  },
      +  "type": "object"
      +}
  8. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description correctly spends its budget on data-quality behavior: coverage_level states ('full'/'basic'/'none'), the analyzed_count vs preliminary_count split, preliminary_band for basic highlights, and not_found semantics. This is genuine interpretive context; it overlaps somewhat with the output schema's field definitions but adds the honesty caveat an agent needs to avoid over-claiming.

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?

Front-loaded with purpose, then usage and routing, then the coverage-semantics detail. The final coverage sentence is dense but every clause carries decision-relevant meaning (distinguishing full/basic/none and not_found).

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?

Given an output schema already exists, the description needn't restate return values, yet it adds the coverage-interpretation layer plus clear routing to siblings. Complete for an agent to select and call it correctly, with only minor redundancy against the schema.

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% with a single well-documented 'area' parameter (formats, disambiguation guidance, shared-name behavior). The description adds no syntax beyond the schema, so the baseline of 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+resource ('Get aggregate dining statistics for a neighborhood, city, or region') and enumerates the returned aggregates (cuisine breakdown, grade distribution, price range, top neighborhoods, highlights). It also implicitly distinguishes itself from the restaurant-level siblings, so an agent can tell it is an area-aggregate tool.

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?

Explicitly states the intended use ('what is the dining scene like in Shoreditch?'), the exclusion ('NOT for finding a specific restaurant or getting a personal recommendation'), and names the alternative with a concrete routing example ('find me a quiet Italian near Shoreditch' → recommend). Nothing is left 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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