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SceneF — San Francisco Movie Showtimes

Right now

scenef_now
Read-only

Check what's playing in San Francisco now. Get tonight's screening count, next five showtimes city-wide with venue/time/film, and data freshness. Detailed mode adds confidence and verified timestamps.

Instructions

The cheap is-anything-on call: how many screenings tonight, the next 5 curtains city-wide with venue/time/film, and dataset freshness per source. In "detailed" mode every showtime also carries its confidence level, source tier, reporting sources, and verified_at timestamp.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
response_formatNoOutput size: "concise" (default) for tight text lines, "detailed" to add ids, per-showtime ticket urls, and extra metadata.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourcesYes
night_ofYes
data_as_ofYes
is_tonightYes
attributionYes
accuracy_urlYes
next_curtainsYes
still_to_comeYes
screenings_tonightYes
Install Server

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description goes beyond them by explaining response composition: counts, next curtains, freshness, and the additional fields in detailed mode. It also discloses the cheap/summary nature of the call, 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 tight sentences, front-loaded with the most important identity ('cheap is-anything-on call') followed by concrete outputs and the mode difference. Every sentence adds information and there is no fluff.

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?

For a single-parameter, read-only tool with an output schema, the description covers the core functionality, the data scope, and the difference between the two response formats. It does not mention edge cases like timezone interpretation or what 'city-wide' means, but those are minor given the surrounding schema and sibling context.

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% and the response_format parameter is already well described in the schema. The description adds extra semantic value by specifying what 'detailed' mode includes (confidence level, source tier, reporting sources, verified_at timestamp), which is not in the schema.

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 the exact purpose with specific verbs and resources: 'cheap is-anything-on call', counts of screenings tonight, next 5 curtains city-wide with venue/time/film, and dataset freshness per source. The scope ('tonight', 'next 5 curtains') clearly distinguishes it from sibling tools like whats_playing or coming_soon.

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 implies when to use it ('cheap is-anything-on call', 'right now', 'tonight') and what it covers, but it never names alternative tools or states when NOT to use it. Siblings exist and some overlap is plausible, so more explicit routing would improve this dimension.

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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