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Ticket prices

ticket_prices

Resale ticket prices for an artist, sports team, comedian or show, from Vivid Seats: each upcoming event's date, venue and city, the cheapest ticket (all in, with fees), the median and highest price, and how many tickets are for sale. place: only events in a city ('Chicago'). limit: up to 40. Uses one read and saves the result in the user's Puley history.

Input Schema

NameRequiredDescriptionDefault
nameYes
limitNo
placeNo

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?

Annotations declare readOnlyHint=false and openWorldHint=true, and the description usefully explains why a price lookup is not read-only: it consumes one read and writes the result into the user's Puley history. It also discloses the data source (Vivid Seats) and that prices are all-in with fees, adding context the annotations cannot convey.

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?

Purpose and return shape are front-loaded, followed by the two parameter notes and a final behavioral note; every clause carries information. The middle section listing returned fields is dense but not redundant with any structured field, since no output schema exists.

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 no output schema, the description steps in to describe the return payload field by field, and with no annotation explaining the write side effect it explains the history save and the one-read cost. For a three-parameter lookup tool this covers what an agent needs before calling it.

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 must carry the parameter burden. It does clarify place (city-only filter with an example, 'Chicago') and limit (hard cap of 40, default 20 shown only in schema), but it never states what 'name' expects precisely (artist vs. team vs. show title) or the matching behavior, so coverage is partial.

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 names a specific verb+resource (resale ticket prices for an artist, team, comedian or show) and enumerates the returned fields (date, venue, city, cheapest all-in price, median, highest, ticket count), so the agent knows exactly what data comes back. It does not differentiate itself from plausible siblings such as resale_prices or find_events, which is why it stops short of a 5.

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?

Usage is implied by the domain ('prices for a show') and two parameters get inline guidance (place restricts to a city, limit caps at 40). There is no explicit when-to-use/when-not guidance and no pointer to the sibling resale_prices or find_events for related tasks, leaving the agent to infer selection.

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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