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BACH-AI-Tools

Realty In Au MCP Server

agencyget_listings

Retrieve property listings for a specific real estate agency in Australia, filtering by sale, rent, or sold properties with timeframe options.

Instructions

Get listings of an agency

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoFor paging purpose1
channelNoOne of the following : SOLD|BUY|RENT
agencyIdYesThe value of agencyId returned in .../agency/list endpoint
timeframeNoOne of the following : -12|-9|-6|-3 (Only function with channel as SOLD)
pageSizeNoThe number of items returned per page, for paging purpose20
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 states 'Get listings' which implies a read-only operation, but doesn't cover critical aspects like authentication requirements, rate limits, pagination behavior (implied by 'page' and 'pageSize' but not explained), error handling, or what the output looks like (no output schema). This leaves significant gaps for safe and effective use.

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 single, efficient sentence ('Get listings of an agency') that is front-loaded and wastes no words. However, it's overly concise to the point of under-specification, missing context that could aid understanding without becoming verbose.

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 tool's complexity (5 parameters, no output schema, no annotations), the description is incomplete. It doesn't explain the output format, pagination details, or behavioral constraints (e.g., authentication). While the schema covers parameters well, the lack of annotations and output schema means the description should compensate more to ensure the agent can use it correctly, which it fails to do.

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 description coverage is 100%, so parameters are well-documented in the schema itself (e.g., 'channel' and 'timeframe' enums, 'agencyId' source). The description adds no additional meaning beyond the schema, such as explaining relationships (e.g., 'timeframe' only works with 'SOLD') or usage tips. Since the schema does the heavy lifting, a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get listings of an agency' states the verb ('Get') and resource ('listings of an agency'), which clarifies the basic purpose. However, it's vague about what 'listings' entails (e.g., property listings, job listings) and doesn't distinguish it from sibling tools like 'agentsget_listings' or 'propertieslist', leaving ambiguity in scope and differentiation.

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. It doesn't mention prerequisites (e.g., needing an agencyId from 'agencylist'), exclusions, or comparisons to similar tools like 'agentsget_listings' or 'propertieslist', leaving the agent to infer usage from parameters 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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