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AIBuilder Marketplace: software pricing dossiers

estimate_cost

Read-onlyIdempotent

Cost of each plan at a team size (or companies/orders, per the product's axis) on monthly or annual billing: monthly equivalent, amount billed per period, commitment, minimums, add-ons and usage. Only for products with price rules; says so otherwise. Never guesses between published price steps: returns a range.

Input Schema

NameRequiredDescriptionDefault
unitsYes
usageNo
addonsNo
billingNoannual
plan_idNo
product_idYes
include_personalNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior. Beyond that, the description adds genuinely useful behavior: it will not interpolate between published price steps and returns a range instead, and it explicitly reports when price rules are absent. Those are non-obvious response behaviors that the annotations do not cover.

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?

Three tight sentences, front-loaded with the core purpose, then return contents, then scope and the range caveat. Dense but no filler; every clause carries information.

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, 0%-coverage schema with no output schema, the description usefully explains the return shape and price-rule caveat. It still leaves two parameters (plan_id, include_personal) and the exact units semantics undocumented, which is a real gap given that no structured field compensates.

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 0%, so the description carries the burden. It meaningfully maps units ('team size, or companies/orders per the product's axis') and billing ('monthly or annual'), and mentions usage and add-ons implicitly. But plan_id and include_personal are never explained, and the meaning of the axis-switching for 'units' is left vague.

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 concrete verb+resource ('Cost of each plan at a team size') and enumerates the return contents (monthly equivalent, amount billed per period, commitment, minimums, add-ons, usage). It also scopes itself ('Only for products with price rules'). However, it never names or contrasts with siblings like compare_offer_costs or cost_at_growth, so an agent must infer the boundary itself.

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 scoping clause 'Only for products with price rules; says so otherwise' gives one real usage condition, which is better than nothing. But there is no explicit when-to-use guidance or routing to alternatives such as compare_offer_costs or cost_at_growth, leaving the agent to guess when estimation vs comparison is appropriate.

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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