Kolmo Construction

Natural-language project parser

parse_project_description

Read-onlyIdempotent

Parse a homeowner's natural-language project description into structured permit-relevant fields: projectType (kitchen|bathroom|deck|adu|fence|...), areaSqft, heightClass, attached/detached, position, and materials. Returns confidence + a single clarifyingQuestion when the parse is ambiguous. Use this before calling check_permit_requirements / estimate_permit_fee when you only have free text from the homeowner. Backed by Gemini 2.5 Pro with a constrained JSON schema.

Input Schema

TableJSON Schema

Name	Required	Description
`cityName`	No	City name (e.g., "Seattle", "Bellevue")
`zoningCode`	No	Zoning code from lookup_parcel_by_address (e.g., "NR2", "LR1")
`description`	Yes	Free-text project description (e.g., "I want to add a 200 sqft deck off my master bedroom on the second floor")
`jurisdictionSlug`	No	Jurisdiction slug from lookup_parcel_by_address (helps disambiguate region-specific terminology)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`parsed`	No
`nextSteps`	No
`attribution`	Yes
`validProjectTypes`	Yes

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already convey read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond that: it returns confidence plus a single clarifyingQuestion when ambiguous, and it is backed by Gemini 2.5 Pro with a constrained JSON schema—helping the agent anticipate output shape and reliability.

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?

Three tight sentences: purpose with field list, return behavior, and usage guidance. Front-loaded and free of filler, every sentence earns its place.

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?

With an output schema, complete schema descriptions, and annotations handling structured details, the description covers the remaining essentials: when to use, what it returns, and the underlying model. No critical context is missing 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%, so all four parameters are already documented in the input schema. The description does not add parameter-level detail, so the baseline of 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?

States a specific verb ('Parse') and resource ('homeowner's natural-language project description'), enumerates the structured output fields, and distinguishes itself from downstream siblings like check_permit_requirements and estimate_permit_fee by positioning itself earlier in the pipeline.

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?

Explicitly instructs: 'Use this before calling check_permit_requirements / estimate_permit_fee when you only have free text from the homeowner.' This names the alternatives and the exact condition that selects this tool, leaving no ambiguity about when to invoke it.

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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