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cinema_showtimes

Retrieve showtimes for one cinema on a chosen date, optionally filtered by a single film. Provides exact published times for planning a movie visit.

Instructions

All showtimes at one cinema for one date.

With film_id: only that film. Without: every film playing that day. Times are as published by the cinema; times after midnight belong to the previous day (cinema day = 03:00-02:59).

Args: cinema_id: MovieGlu numeric cinema id. date: YYYY-MM-DD (defaults to today). film_id: Optional film id to narrow the schedule to one film. sort: popularity or alphabetical.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNo
sortNo
film_idNo
cinema_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden. It discloses key behaviors: times are 'as published by the cinema,' after-midnight times belong to the previous day with a defined cinema day (03:00-02:59), and date defaults to today. These are not visible in the schema and are essential for correct invocation and interpretation.

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 description is a compact paragraph that front-loads the core purpose, then lists parameters in a clean bullet-like structure. Every sentence adds information—there is no fluff. The cinema-day note is placed early where it matters, and the args section is easy to scan.

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?

For a 4-parameter tool with an existing output schema, the description covers all operational details an agent needs: scope, filtering behavior, defaults, sort choices, and the special day-boundary rule. No critical context is missing, and the output schema handles return structure.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, yet the description's 'Args' section fully compensates: it explains cinema_id as 'MovieGlu numeric cinema id,' date format and default, film_id as optional narrowing, and sort options ('popularity or alphabetical'). This goes far beyond the bare schema types and defaults.

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 opens with 'All showtimes at one cinema for one date,' which is a specific verb+resource+scope, and immediately clarifies the effect of film_id ('With film_id: only that film. Without: every film playing that day.'). This unambiguously distinguishes it from siblings like movie_showtimes (which likely covers multiple cinemas) and closest_showing.

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 description explains how to narrow the schedule with film_id and provides the cinema-day definition, but it never explicitly states when to use this tool instead of alternatives such as movie_showtimes or closest_showing. The 'at one cinema' phrase implies a constraint, but no direct comparison or exclusion is given, leaving the agent to infer routing.

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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