SceneF — San Francisco Movie Showtimes

Film details

scenef_film_details

Read-only

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

Name	Required	Description	Default
`film`	Yes	Film title or SceneF slug.
`response_format`	No	Output size: "concise" (default) for tight text lines, "detailed" to add ids, per-showtime ticket urls, and extra metadata.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`film`	No
`query`	Yes
`matched`	Yes
`showtimes`	No
`candidates`	No
`data_as_of`	Yes
`attribution`	Yes
`final_night`	No
`accuracy_url`	Yes
`is_last_night`	No
`showtime_count`	No

TDQS

A4.1/5.0

Behavior3/5

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

There are no annotations shown, so the description must carry the burden of behavioral disclosure. It does include useful behavioral detail such as 'when present', a 'last-night flag', and mode-dependent showtime fields, but it does not disclose other behavioral traits like read-only nature, possible absences, or error behavior.

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?

The description is dense rather than verbose; it bundles a comprehensive field list into two sentences without repetition. The conditional qualifiers like 'when present' and 'when the run is ending' are meaningful and not wasted words.

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?

Given no output schema is provided, the description does a strong job of telling the agent what the response will contain for both concise and detailed modes. It is complete enough for a single-card retrieval operation, though it could have added explicit notes about defaults or fallback behavior if showtimes are absent.

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?

The input schema already describes both parameters: 'film' accepts a title or slug, and 'response_format' controls concise vs detailed mode. The description adds extra semantic value by explaining what 'detailed' mode actually includes, such as confidence level, source tier, reporting sources, and verified_at timestamp.

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 that the tool returns 'the full card for one film' and then enumerates the exact set of fields and content it contains. This clearly identifies the tool's purpose and distinguishes it from sibling tools that handle search, showtime lookup, or venue info.

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 provides clear context: use this tool when you need the complete card for a single film, including showtimes, credits, rating, and poster. It does not explicitly state when not to use this tool versus its siblings, but the single-film scope and full-card framing make the intended use obvious.

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

All SceneF — San Francisco Movie Showtimes tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0

Disambiguation4/5

Most tools have clearly distinct query shapes: film lookup, theater card, discount list, coming-soon radar, and recommendation planner are easy to separate. Some overlap exists because several tools expose showtimes from different angles (e.g. scenef_whats_playing vs. scenef_now, and scenef_film_details vs. scenef_search_showtimes), but the descriptions provide enough grounding that an agent can usually select correctly.

Naming Consistency3/5

Every tool is prefixed with scenef_ and uses snake_case, which gives a consistent visual identity. Nevertheless, the pattern after the prefix is mixed: some names are nouns (scenef_discounts, scenef_accuracy), some are time references (scenef_now, scenef_coming_soon), and some are verb-first (scenef_search_showtimes, scenef_plan_movie_night). It is readable but not a single predictable verb_noun convention.

Tool Count5/5

Nine tools is right in the ideal range and each tool earns its place in the SF showtimes domain. The set covers discovery, detail lookups, discounts, recommendations, and data-accuracy verification without feeling padded or bloated.

Completeness4/5

The domain is covered broadly: film discovery, film details, theater details, per-film showtimes, coming soon, discounts, nightly overview, personalized planning, and accuracy metrics. The main gap is that there is no simple cross-film showtimes-for-a-specific-date listing, but agents can usually work around this with scenef_whats_playing and scenef_search_showtimes.

Resources

Need Help?