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Broombook: cleaning business calculators

Commercial cleaning bid calculator

bid_commercial_cleaning
Read-onlyIdempotent

A monthly bid for a commercial cleaning contract (office, medical office, school, retail, gym, church, warehouse) from the cleanable square feet and how often it is cleaned. Returns the monthly price, price per visit, price per square foot, labor hours and profit. Production rates are starting assumptions to replace with timed numbers.

Input Schema

NameRequiredDescriptionDefault
sqftYesCleanable square feet.
facilityNoKind of building: office (Office), medical (Medical or dental office), school (School or daycare), retail (Retail store), gym (Gym or fitness studio), church (Church or event space), warehouse (Warehouse or light industrial). Default office.
marginPctNoTarget profit margin, percent of the price. Default 20.
hourlyWageNoCleaner pay per hour, in dollars. Default 18.
cleaningsPerWeekNoCleanings per week. Default 5.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

The annotations already establish that this is a read-only, idempotent, non-destructive calculation. The description usefully adds the returned metrics and a key caveat that production rates are starting assumptions to replace with timed numbers, though it does not discuss calculation assumptions in more detail.

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?

The definition is two compact sentences that front-load the purpose, then state the return values and an important assumption caveat. Every sentence contributes useful information without excess wording.

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?

Given the fully described schema and no output schema, the description is nearly complete: it explains what the tool computes, what it returns, and the starting-assumption caveat. It could be slightly stronger by explicitly distinguishing commercial use from residential sibling tools, but no critical information is missing.

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 five parameters are already well documented in the input schema. The description reinforces square footage, frequency, and facility type but does not add meaningful semantics beyond what the schema provides, making 3 the appropriate baseline.

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?

The description clearly states that this tool calculates a monthly bid for a commercial cleaning contract using cleanable square feet and cleaning frequency, and it lists the supported facility types. It implicitly separates itself from the residential-focused sibling price_house_cleaning, but does not explicitly name or route against any sibling tool.

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

Usage Guidelines3/5

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

The commercial contract context and facility list imply when the tool should be used, but the description gives no explicit when-not guidance or alternatives such as residential cleaning or state minimum price tools. Usage is understandable but left to inference.

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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