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Smarty Property Enrichment

smarty_property_enrichment
Read-onlyIdempotent

Property attributes (year built, sqft, value, owner) for a US address — returns 350+ data points from tax assessor & deed records including bedrooms/bathrooms, lot size, assessed & market value, and last sale. Example: smarty_property_enrichment({ street: "1400 Sandhill Rd", city: "Orem", state: "UT", _apiKey: "authId:authToken" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoCity name (optional if included in street)
stateNoState abbreviation or name (optional)
streetYesStreet address, or a full freeform US address, e.g. "1400 Sandhill Rd" or "1400 Sandhill Rd, Orem, UT 84058"
_apiKeyYesSmarty credentials as "authId:authToken" (server key pair), or a single embedded/website key. Free account + 1000 lookups at smarty.com
zipcodeNoZIP Code (optional)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations declare readOnlyHint:true, idempotentHint:true, and destructiveHint:false, covering the safety profile. The description adds some context by specifying the data sources (tax assessor & deed records) and the breadth of data (350+ points), but doesn't disclose additional behaviors beyond what annotations already provide.

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?

Two sentences plus an example, with zero wasted words. The primary purpose and key data points are front-loaded, and the example illustrates input format effectively. Very efficient and well-structured.

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

Completeness3/5

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

With no output schema, the description could elaborate on the return structure, but it does list many specific data points (bedrooms/bathrooms, lot size, assessed & market value, last sale) which gives a good idea. However, it lacks details on error handling, rate limits (though the free account is mentioned in schema), or pagination. Adequate but with room for improvement.

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%, so all parameters are already documented. The description provides an example that clarifies variable usage (e.g., passing street only or full address) and mentions the free account tier, but this is also covered in the schema's _apiKey description. No additional meaning beyond schema is added.

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 property attributes for a US address, with specific examples of data points (year built, sqft, value, owner, etc.). It distinguishes itself from the sibling tool smarty_verify_address by focusing on property enrichment rather than address verification.

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

Usage Guidelines3/5

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

The description implies usage through an example (smarty_property_enrichment({ street: ... })) but does not explicitly state when to use this tool versus alternatives like smarty_verify_address. No mention of conditions or exclusions; the context is implied rather than stated.

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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