Skip to main content
Glama
speedwarnsf

SceneF — San Francisco Movie Showtimes

Film details

scenef_film_details
Read-only

Retrieve a film's full record—title, year, runtime, cast, rating, trailer, and every verified showtime with venue and ticket link. Use detailed mode for confidence and source metadata.

Instructions

The full card for one film: title, year, runtime, genres, directors, cast, overview, rating, trailer and poster urls when present, every upcoming showtime with venue/time/ticket link, and a last-night flag when the run is ending. In "detailed" mode every showtime also carries its confidence level, source tier, reporting sources, and verified_at timestamp.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filmYesFilm title or SceneF slug.
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
filmNo
queryYes
matchedYes
showtimesNo
candidatesNo
data_as_ofYes
attributionYes
final_nightNo
accuracy_urlYes
is_last_nightNo
showtime_countNo
Install Server

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral detail by noting optional presence of URLs, the conditional last-night flag, and exactly what differs in 'detailed' mode, which helps the agent anticipate variable output.

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 tightly-packed sentences with no filler. The core purpose and field list are front-loaded, and the detailed-mode distinction is placed at the end without redundancy.

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?

Given the output schema, annotations, and sibling context, the description fully covers what the agent needs to know to invoke this tool correctly. It explains the one-film scope, the optional mode difference, and the conditional fields without relying on the schema alone.

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 100%: both `film` and `response_format` already have meaningful descriptions and enums. The description reinforces the mode behavior but does not add new parameter meaning beyond the schema, so baseline 3 is appropriate.

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 clearly identifies the tool as returning a complete card for a single film, listing all included fields (title, year, runtime, genres, directors, cast, overview, rating, trailer/poster URLs, showtimes, last-night flag). This specific scope differentiates it from sibling list/search tools like scenef_whats_playing or scenef_search_showtimes.

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 clear usage context: use this when you need the full detail set for one specific film, including showtimes and metadata. It does not explicitly name alternatives or state when not to use it, but the 'one film' framing provides enough contextual guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/speedwarnsf/scenef-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server