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BACH-AI-Tools

Zillow56 MCP Server

market_data_rental_market_trends

Analyze rental market trends by retrieving current rental data for specific cities or ZIP codes to inform real estate decisions.

Instructions

Get market rental data of a location by city or ZIP

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
locationYesExample value: houston, tx
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'Get' which implies a read-only operation, but fails to describe any behavioral traits such as data freshness, rate limits, authentication needs, or what 'market rental data' entails (e.g., trends, averages, listings). This leaves significant gaps in understanding how the tool behaves.

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?

The description is a single, efficient sentence with no wasted words. It front-loads the core purpose ('Get market rental data') and includes essential details ('of a location by city or ZIP'), making it easy to parse quickly. Every part of the sentence contributes directly to understanding the tool's function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of market data tools, no annotations, and no output schema, the description is incomplete. It lacks details on what the tool returns (e.g., data format, metrics like median rent or trends), behavioral constraints, or how it differs from similar tools. This leaves the agent with insufficient context to use the tool effectively without trial and error.

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 input schema has 100% description coverage, with the 'location' parameter documented as 'Example value: houston, tx'. The description adds minimal value by specifying 'by city or ZIP', which slightly clarifies the parameter's semantics beyond the schema. Since schema coverage is high, the baseline score of 3 is appropriate, as the description compensates only marginally.

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?

The description clearly states the action ('Get') and resource ('market rental data of a location'), specifying it can be by city or ZIP. It distinguishes itself from siblings like 'market_sale_overview' by focusing on rental data rather than sale data. However, it doesn't explicitly differentiate from 'rent_estimate_rent_zestimate', which might overlap in purpose.

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 description provides no guidance on when to use this tool versus alternatives such as 'rent_estimate_rent_zestimate' or 'search_search_for_properties_by_neighborhood_city_or_zip'. It lacks context on prerequisites, exclusions, or specific scenarios where this tool is preferred, leaving the agent to infer usage from the tool name alone.

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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