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Verified-review statistics for a city

get_local_agent_review_data
Read-only

Returns Rate-My-Agent.com's verified-review statistics for one city: how many reviewed agents and verified reviews exist there and site-wide, the average rating, the most-reviewed neighbourhoods, and whether the free matching service covers that city (it covers every US and Canadian city). Call it when the user asks about real estate agents in a specific place, or before running the matching questionnaire, to show what the ratings are based on. It returns aggregate statistics only — it does not return, rank or recommend individual agents. To collect the user's requirements, call get_matching_questions next.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYesCity name, e.g. "Austin" or "Vancouver".
prov_stateYes2-letter province/state code, e.g. "BC", "TX".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNo
coverageNo
city_proofNo
prov_stateNo
network_proofNo
adapter_versionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and non-destructive nature. The description adds valuable context beyond that: the aggregate-only scope (no individual agents), the city coverage claim (every US/Canadian city), and the purpose of showing what ratings are based on. It doesn't describe output structure, but an output schema exists, so that's not required.

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?

The description is a bit longer than necessary but well-structured: the first sentence lists return values, the second covers when to use, the third clarifies limitations, and the fourth gives the next step. Each sentence earns its place, though it could be slightly more terse without losing value.

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 the tool's moderate complexity, with full schema coverage and an output schema, the description covers what it returns, when to use it, what it does not do, and the next step. No critical missing information for an agent to invoke it correctly.

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?

The schema already provides full parameter descriptions for city and prov_state with examples, and coverage is 100%. The description does not add meaningful parameter-level semantics beyond the tool's purpose (e.g., it doesn't specify input formats beyond schema). Baseline 3 is appropriate since the schema does the heavy lifting.

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 tool returns verified-review statistics for one city, enumerating specific data points (reviewed agents, verified reviews, average rating, top neighbourhoods, service coverage). It explicitly contrasts with siblings by noting it does not return, rank, or recommend individual agents, making its purpose unmistakable.

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?

Provides explicit guidance on when to call: 'when the user asks about real estate agents in a specific place, or before running the matching questionnaire.' It also names the sibling next step: 'To collect the user's requirements, call get_matching_questions next.' This fully covers selection and 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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