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Get price quote

get_price_quote
Read-onlyIdempotent

Price a hypothetical survey without creating anything: incidence estimate, LOI, cost per complete (CPI), total, feasibility and warnings. Minimum 100 completes, maximum 75 questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetingNoOptional demographic targeting — narrows incidence and raises the price.
country_codeYesISO-2 country code (from get_survey_options).
question_countNoPlanned number of questions (1-75). Omit for a 10-question estimate.
submissions_quotaYesTarget number of completes (minimum 100).
has_location_targetingNoTrue if postcode/region targeting will be used (adds a warning only).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description doesn't need to repeat that. It adds value by specifying the exact outputs (incidence, LOI, CPI, total, feasibility, warnings) and constraints (min 100 completes, max 75 questions). It also explains the effect of targeting on incidence and price, which is useful behavioral context.

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?

Two sentences, front-loaded with purpose and output, followed by constraints. No wasted words. Highly scannable.

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 rich schema and annotations, the description covers the core purpose and constraints. It lacks details about output format or how to interpret the quote, but for a pricing tool this might be sufficient. The absence of an output schema means the description could have clarified the return structure, but it lists key metrics, which is helpful.

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 coverage is 100%, so parameters are well-described. The description adds usage nuances: 'Omit for a 10-question estimate' for question_count, 'adds a warning only' for has_location_targeting, and explains targeting's effect on incidence/price. This exceeds the schema's basic descriptions.

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?

The description states a specific verb ('Price') and resource ('hypothetical survey'), and explicitly distinguishes itself from creation tools by saying 'without creating anything'. This clearly separates it from siblings like create_survey and launch_survey.

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?

The description implies the tool is for pre-creation pricing, but doesn't explicitly name alternatives or exclusions. It's clear enough that this is the pricing step before creating, but could benefit from explicit guidance on when not to use it (e.g., when you need to create the survey).

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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