SceneF — San Francisco Movie Showtimes

Discount grid

scenef_discounts

Read-only

Every structured discount across all SF theaters — venue, label, detail, and day-bound days — with the ones that apply today flagged.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`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
`venues`	Yes
`today_dow`	Yes
`data_as_of`	Yes
`today_name`	Yes
`attribution`	Yes
`accuracy_url`	Yes
`applies_today_count`	Yes

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already declare this as safe read-only and non-destructive. The description adds useful behavioral context: it returns all structured discounts, not just today's, and marks the ones currently applicable. This clarifies a potential edge case where an agent might assume the tool only returns today's discounts.

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?

In one concise sentence, the description establishes the scope (all SF theaters), the content (venue, label, detail, day-bound days), and the key behavior (today's discounts flagged). There is no filler or repeated schema content, and the most important information is front-loaded.

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?

The tool is simple with zero required parameters, full param schema coverage, and an output schema. The description provides enough contextual grounding for what data is included and how today's deals are marked, so an agent can correctly select and invoke the tool.

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 coverage is 100% and the only parameter, response_format, is fully described in the schema with concise and detailed modes. The tool-level description does not need to repeat parameter details and adds nothing beyond the schema, so baseline 3 applies.

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 clearly defines the scope: every structured discount across all SF theaters, including the fields returned such as venue, label, detail, and day-bound days. It also notes today-applicable discounts are flagged. However, it has no explicit verb like 'lists' or 'retrieves', and instead uses a fragment, which slightly weakens the purpose clarity.

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 phrase 'across all SF theaters' gives clear context that this tool is the comprehensive discount lookup covering every venue. It does not explicitly name alternative tools, but the discount-specific scope makes when to use it apparent. There are no exclusions or alternative paths described.

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

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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

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