MappaIQ

Create BOV report

generate_bov

Create a Broker Opinion of Value (BOV) comparable-sales PDF: a comp table, price and $/acre ranges, and your analyst commentary. Use when the user asks for a BOV, comp exhibit, or comp-set PDF. First pick the comp set (search_comps / analyze_comps), then write the commentary yourself: 2-3 professional sentences on the pricing range, $/acre range, notable trends, and zoning or asset-type observations — it goes straight into a client-facing document. Pass compIds (preferred) or a layerId. Max 100 records. The PDF appears as a download button in the chat.

Input Schema

Name	Required	Description
`title`	No	Header subtitle, e.g. the layer name or subject property
`compIds`	No	The comp IDs in the set
`context`	Yes	Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
`layerId`	No	Use every comp in this layer instead of compIds
`llm_model`	Yes	The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
`commentary`	Yes	2-3 sentence analyst commentary paragraph, no headers or labels
`conversation_id`	No	Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 17, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations only declare readOnlyHint=false and destructiveHint=false; the description adds real behavioral context beyond that — a 100-record cap, that the PDF surfaces as a download button in chat, and that the commentary lands in a client-facing document (implying a quality bar). It does not cover permissions or failure modes, so it stops short of a 5.

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?

Front-loads what the tool produces before the usage trigger and the parameter guidance, so an agent can decide early. It is somewhat dense with multiple clauses, but nearly every sentence carries actionable information rather than 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?

With 7 params, no output schema, and a mutation-adjacent generation task, the description supplies the missing pieces: the output form (chat download button), the input limit, and the sequencing dependency. The remaining params (title, context, llm_model, conversation_id) are well covered by the schema itself, so nothing critical is absent.

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 coverage is 100%, so the baseline is 3, but the description adds meaning the schema does not: the compIds-vs-layerId preference, the 100-record limit, and concrete content guidance for commentary (2-3 sentences covering pricing range, $/acre, trends, zoning/asset-type).

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 (create) and a concrete artifact (BOV comparable-sales PDF) and enumerates its contents: comp table, price and $/acre ranges, analyst commentary. This distinguishes it from siblings like analyze_comps (analysis only) and generate_file (generic file output).

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?

Gives an explicit trigger ('user asks for a BOV, comp exhibit, or comp-set PDF') and an ordered prerequisite workflow: pick the comp set via search_comps / analyze_comps first, then write commentary. It also names the parameter alternative and its preference ('compIds (preferred) or a layerId').

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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