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dealmachine_enrich_latlng

Destructive

Finds the property closest to a latitude and longitude, within 300 feet, and who owns it. Returns the property details; with contact_audience=owners it also returns the owners with their names, phones (with DNC flags) and emails. Contacts are left out unless contact_audience is set. Needs a connected DealMachine account with paid access. A matched property costs one property credit and returned contacts cost people credits; nothing is charged when no property matches.

Input Schema

NameRequiredDescriptionDefault
fieldsNoDealMachine property field IDs to include in results
latitudeYesLatitude
longitudeYesLongitude
contact_audienceNo`none` returns property-only data with zero people credits; other values include matching contacts

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Adds substantial behavior beyond the annotations: the 300-foot match radius, the requirement of a connected DealMachine account with paid access, the per-match property credit and per-contact people-credit cost model, and the fact that nothing is charged on a no-match. That credit-charging model is exactly the destructive consequence implied by destructiveHint=true, and it is disclosed explicitly rather than left to the annotation.

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?

Four sentences, each carrying distinct information: what it matches, what it returns, the contact gating rule, and the preconditions/cost. Front-loaded with the core action and no filler.

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?

There is no output schema, so the description correctly compensates by describing the return shape (property details, and owner contacts with DNC flags when requested). It covers prerequisites and cost but says nothing about match ambiguity, tie-breaking between multiple properties inside 300 feet, or the practical meaning of the fields array.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema coverage the schema already documents all four parameters, so the baseline is 3. The description earns a bump by explaining the behavioral effect of contact_audience (owners yields names/phones/emails; unset yields property-only) rather than just restating the enum values.

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?

States a specific verb and resource (finds the property closest to a lat/lng and its owner) plus a concrete scope constraint: within 300 feet. The coordinate-based input inherently separates it from the address/APN/name/phone enrichment siblings, so an agent can pick it without opening a schema.

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?

Gives clear conditional guidance: contacts are omitted unless contact_audience is set, and contact_audience=owners is the path to get owner names, phones with DNC flags, and emails. It stops short of naming sibling alternatives (e.g. enrich_address for a street address, or reverse_geocode), so the agent must infer which enrichment tool fits when it has an address instead of coordinates.

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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