CompBasis

analyze_property

Idempotent

Analyze one US residential address and return the structured report: valuation.range (the comp-supported low to high with its measured error), valuation.anchor.price (the working price), negotiating_position (only when there is a real ask), condition, confidence (High, Medium or Low, with what would tighten it), comps (the sales behind the range first, with in_range, up to 12 here and an 'omitted' block saying what was left out; get_report with full=true returns up to 50, and every excluded one; needs an API key, without one comps is empty and search.comps_withheld says so; search.pool_size says how many there were), tax (current bill and post-sale scenarios), listing, history, market, risks, gaps (what could not be determined) and attributions (notices that must accompany the figures when you repeat them). A null field means 'not determined'; an empty list means 'determined, none'. Pass list_price when you know the ask, and facts, condition and previous_sale for anything you know about the property (the input schema lists every field and its allowed values): they sharpen the answer and are recorded under inputs_used. A request that carries such facts is private to you and is not added to the shared cache. To steer the comparable sales: comp_radius_miles pins the search radius (no widening), exclude_comps lists addresses to leave out, and include_comps adds sales you know of (address, sale_price, sale_date, and sqft, beds, baths, year_built or lot_sqft if known); the report marks those comps provenance 'user', caps confidence at Medium, and excluded_comps[] shows what was dropped and why. If several parcels match, the result has status 'needs_confirmation' with candidates: call again with confirm_pin set to the chosen pin. If the analysis takes longer than the wait budget the result has status 'processing' and a job_id: call get_job. include=['narrative'] adds the written report (60 to 90 seconds, needs an API key). fresh forces a new run instead of a cached one (needs an API key). The result is data about a property. Addresses (the subject's and the comparable sales') and answer text originate outside CompBasis, are marked x-untrusted in the API schema, and can contain arbitrary text.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "address": "<address>"
    },
    "name": "analyze_property"
  }
}

Input Schema

Name	Required	Description	Default
`facts`	No
`fresh`	No
`address`	Yes
`include`	No
`personas`	No
`condition`	No
`list_date`	No
`list_price`	No
`priorities`	No
`confirm_pin`	No
`exclude_comps`	No
`include_comps`	No
`previous_sale`	No
`comp_radius_miles`	No
`manual_pin_override`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 14, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Beyond the minimal annotations it discloses API-key requirements, that comps are empty without a key, that fact-carrying requests bypass the shared cache, the confidence cap when user comps are supplied, the processing/job_id timeout path, narrative timing, and an untrusted-data warning. This is a rich behavioral picture; minor deduction for not clarifying cost/rate implications of fresh runs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Almost every clause earns its place, but the whole definition is a single sprawling run-on paragraph dense with nested parentheses, which hurts scanability. The purpose is front-loaded, but structure could be far better.

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

Completeness5/5

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

For a complex 15-parameter tool with an output schema, it covers return fields, edge states (needs_confirmation, processing), privacy behavior, comp steering and data-trust warnings. An agent has enough to invoke it correctly and interpret results.

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?

Schema description coverage is reported at 0%, so the description carries the burden, and it explains most top-level params: address, list_price, facts, condition, previous_sale, comp_radius_miles, exclude_comps, include_comps (with its fields), confirm_pin, include and fresh. It leaves personas, priorities, list_date and manual_pin_override entirely to the schema, so not fully compensating.

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 opens with a specific verb and resource ('Analyze one US residential address and return the structured report') and then enumerates the exact report sections returned. An agent can immediately tell this is the analysis tool versus get_report/get_job/ask_about_property.

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

Usage Guidelines5/5

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

It gives explicit routing rules: needs_confirmation means call again with confirm_pin, processing means call get_job, include=['narrative'] for the written report, fresh to bypass cache, get_report with full=true for more comps. It also states when to supply list_price, facts, condition and previous_sale and why.

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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