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areshms

RE Data Refinery MCP Server

refinery_search_properties

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Search Columbus, OH properties using natural language queries to identify scored, AI-ready investment opportunities. Results are cached and available as markdown or JSON.

Instructions

Search for scored Columbus, OH properties using natural language terms.

This is a paid lookup ($0.50 via x402) unless REFINERY_ENABLE_X402=false. Results are written through to the Refinery cache.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the annotations, the description discloses two important behavioral traits: this is a paid lookup costing $0.50 via x402 unless REFINERY_ENABLE_X402=false, and results are written through to the Refinery cache. These are valuable operational details that affect invocation decisions and are not present in the structured fields.

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 three concise sentences with no filler. The primary action is front-loaded, followed by the cost condition and cache side effect, making it easy for an agent to parse quickly.

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?

The description covers purpose, cost, payment bypass condition, and cache behavior, and the output schema handles return-value details. It does not explicitly guide an agent toward sibling alternatives or define what 'scored' means, but for a search tool with this schema, the essential context is present.

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 description adds some parameter meaning by specifying that the search uses natural language terms, which directly informs the query parameter. However, it does not describe limit or response_format; the nested input schema provides those details, so the description is sufficient but not rich.

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 states a specific verb ('Search'), a specific resource ('scored Columbus, OH properties'), and a distinctive method ('using natural language terms'). This separates it from sibling tools like list_properties or get_property, which imply different operations.

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

Usage Guidelines4/5

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

The description clearly positions this as the natural-language search tool for scored Columbus, OH properties, providing enough context for an agent to select it over a plain list/get tool. It does not explicitly name when-not-to-use alternatives, but the core usage context is clear.

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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