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Kolmo Construction

Renovation ROI

get_project_roi
Read-onlyIdempotent

Get the estimated return on investment (ROI) for a home remodeling project in the Seattle area. Based on Remodeling Magazine Cost vs. Value data for the Pacific Northwest. Helps homeowners decide which projects add the most resale value — e.g. "What ROI does a kitchen remodel get in Seattle?" or "Which remodel pays off the most?"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectTypeNoType of project, e.g. "kitchen", "bathroom", "deck", "windows", "siding", "ADU", "basement". Omit to see all projects ranked by ROI.
estimatedCostNoYour estimated project budget in USD. If provided, returns expected resale value added.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketYes
sourceYesThird-party dataset. Cite it alongside Kolmo.
resultsNo
disclaimerYes
attributionYes
neighborhoodNo
getAccurateQuoteYes

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already mark the tool read-only and idempotent, and the description adds the important geographic limitation (Seattle area / Pacific Northwest) and the fact that the value is an estimate based on Remodeling Magazine data. It does not contradict annotations, and the output schema covers the return shape.

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?

Two sentences plus two examples, front-loaded with the core action and scoped immediately. The examples earn their place by illustrating natural-language use, so the description is appropriately sized without padding.

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 an output schema present, read-only annotations, 100% parameter documentation, and a clear statement of scope and data source, an agent has what it needs to select and invoke the tool. The only minor gap is an explicit caveat about data/update limitations, but that is not required for correct invocation.

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%, and both projectType and estimatedCost are already documented with examples and semantics. The description adds no new parameter-level detail, so baseline 3 is appropriate.

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?

Opens with a specific verb, resource, and geographic scope: 'Get the estimated return on investment (ROI) for a home remodeling project in the Seattle area.' It also names the data source and distinguishes itself from generic estimation tools by focusing on resale value for homeowners.

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?

Clearly frames when to use it: to help homeowners decide which projects add the most resale value, with two natural-language examples. It does not explicitly state alternatives or when-not-to-use, so it stops short of a 5.

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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but get_neighborhood_project_activity and get_neighbor_permit_activity are easy to confuse, and get_material_catalog vs get_material_options have overlapping scope. The detailed descriptions mostly resolve ambiguity, so it stays above average.

Naming Consistency4/5

Naming follows a mostly consistent get_/list_ verb-noun pattern, with a small set of other descriptive verbs like check_, estimate_, and resolve_. The neighbor/neighborhood naming collision and a few multi-word exceptions are the main inconsistencies.

Tool Count2/5

At 36 tools, the surface is heavy and exceeds the 25+ threshold, spanning permits, estimates, content, reviews, financing, weather, and procurement. While each cluster has plausible value, the overall count feels bloated for an agent to navigate efficiently.

Completeness4/5

The set covers a broad lifecycle: permit research, estimates, licensing, financing, ROI, weather, project/services content, reviews, and lead submission. Minor gaps like scheduling/booking and direct estimate persistence prevent a perfect score.

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