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Price one or more datasets

get_quote
Read-onlyIdempotent

Line-item prices and total for a list of dataset slugs, each with how it is sold (soldBy: file, row, or both) — the same rule create_checkout, buy_dataset, create_query_checkout and query_locations enforce, so a quote never offers a route checkout refuses. A list sold by the row only (an Overture Maps list) is quoted at its per-row rate with the route named, not as a file; count_locations with filters gives the exact price of the rows. Every list sold by the row is quoted with its perRow rate and the per-call fee, next to any file price. A paid call is billed for the rows it returns: each row at its own list's per-row rate (an Overture open-data row at $0.005; a row of a chain LocationLists sells its own list for, at that list's rate), plus a $0.01 per-call fee, rounded once to the nearest cent, at least $0.02, never more than the whole list. count_locations with the same filters, limit and offset quotes exactly that page, row source by row source (price.breakdown), before anything is paid. How a list is sold: our own lists are sold as a whole file (create_checkout / buy_dataset), and those of 5,000 records or more are also sold by the row (query_locations / create_query_checkout); smaller lists are sold whole only. Open map data lists (soldBy "row" in get_dataset) are sold by the row ONLY, at any size — there is no file to buy. One card checkout downloads up to 10,000 rows at once; up to 150,000 rows, an answer's buy link still sells them all, and the file is built after payment and its download link emailed. For more, buy the whole file where the list has one, narrow the question to a state, metro or area, or email kyle@locationlists.com for the whole file. If a bundle covers several requested brands for less, it says so.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugsYesDataset slugs

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds valuable behavioral detail: pricing rules (per-row, per-call fee, rounding, min $0.02, max list price), how soldBy affects quoting, and checkout limits. However, it does not describe the return structure (line items, total) in a structured way, and some pricing details are verbose but not fully clarifying for an agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is overly long and rambling, with multiple sentences repeating pricing rules and checkout limits. It is front-loaded with the core purpose but then diverges into extensive edge cases, making it hard to scan. Several sentences could be consolidated or moved to a separate pricing guide.

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?

Given the tool's read-only nature, no output schema, and one required parameter, the description is complete enough to call it, but it omits key contextual details: the return shape (line items, breakdown structure), whether the response includes a total, and how errors are handled for invalid slugs. It focuses heavily on pricing rules rather than the tool's output, leaving gaps for an agent to interpret results.

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 coverage is 100%, so the single 'slugs' parameter is fully documented in the schema. The description adds context that slugs represent dataset lists and that soldBy matters, but does not provide additional semantics beyond what the schema already provides for the parameter itself.

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 states a specific verb and resource: 'Line-item prices and total for a list of dataset slugs,' and immediately distinguishes itself by linking to the pricing rule enforced by create_checkout, buy_dataset, and others. It is clear what the tool does, though it does not explicitly name 'get_quote' vs a sibling like count_locations as the alternative.

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 gives clear usage context: it is for quoting prices before checkout, and it names how to get exact row prices via count_locations with filters. It implies when to use this tool (to preview costs) but does not explicitly state when not to use it or name a direct alternative for simple file-only quotes.

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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