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paintbrushv

plat-costmodel

by paintbrushv

estimate_full_property

Calculate a property-level renovation estimate by rolling up unit costs and exterior capital expenses, including roof, parking, HVAC, and other selected items.

Instructions

Property-level estimate rolling up unit costs + exterior CapEx.

Args: property_id: Property identifier total_units: Total units at the property units: List of unit dicts with keys: unit_id, sqft, bedrooms, bathrooms, scope_level, finish_tier year_built: Property year built property_class: "B" or "C" market: "dallas" or "birmingham" exterior_items: Exterior CapEx categories to include (default: all). Options: roof, parking, hvac, siding_paint, fencing_gates, landscaping, signage_lighting

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
unitsYes
marketNo
year_builtNo
property_idYes
total_unitsYes
exterior_itemsNo
property_classNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden, and it is silent on side effects, whether anything is persisted or registered, determinism, auth requirements, or cost/latency. The only behavioral hint is the exterior_items default ('default: all'), which is input semantics rather than tool behavior.

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?

One front-loaded sentence gives the purpose, then a tight Args list; no filler, no repetition of the name, and every line carries information the agent needs to construct the call.

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?

For a 7-parameter computational tool with no annotations and no output schema, the input side is well covered but the output side is entirely absent — the agent is not told the shape of the returned estimate, whether it is per-unit and per-exterior-category, or in what currency/units. Usage context relative to the many sibling estimators is also missing.

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 0%, and the description compensates well: it names every parameter and adds meaning absent from the schema, including the nested unit keys (unit_id, sqft, bedrooms, bathrooms, scope_level, finish_tier) and enumerations the schema lacks ('B' or 'C', 'dallas' or 'birmingham', the seven exterior categories). It stops short of defining allowed values for scope_level/finish_tier or the units of sqft.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: 'Property-level estimate rolling up unit costs + exterior CapEx.' It is clear what is produced, but it never distinguishes itself from near-identical siblings such as estimate_property_from_model, estimate_scope, or estimate_from_deal, so an agent cannot route confidently among them from the description alone.

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

Usage Guidelines2/5

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

There is no when-to-use, when-not-to-use, or alternative-tool guidance anywhere in the text. The Args block documents inputs but leaves the agent to infer the scenario (whole-property renovation budgeting) and gives no hint about when this beats estimate_property_from_model or estimate_scope.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.