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by ai.switchapp
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Apply Movie Scene

apply_movie_scene
Read-onlyIdempotent

Put me in a movie — full cinematic film look matching specific film genres. Choose: neon-noir action thriller, 80s finance excess, comic-book superhero blockbuster, video-game key art, or generic action thriller. Returns the styled prompt stack for your shot and the aspect_ratio to make it at — pair it with generate_image and pass that aspect_ratio along.

Input Schema

NameRequiredDescriptionDefault
styleYesneon_noir_action = wet streets + neon + anamorphic. glamour_finance_excess = 1980s Wall Street mahogany / gold. superhero_blockbuster = comic-book key art. video_game_character = Unreal-Engine character render. generic_action_thriller = ARRI cinematic.
subjectNoWhat you want to shoot. E.g. "a woman walking through a hotel lobby" or "morning coffee on the balcony".
aspect_ratioNoOptional frame shape. Replaces the shape the style uses by default. The answer carries aspect_ratio: pass it to generate_image so the picture is made at that shape.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / aspect_ratio
      Added value: +{
+  "description": "Optional frame shape. Replaces the shape the style uses by default. The answer carries aspect_ratio: pass it to generate_image so the picture is made at that shape.",
+  "enum": [
+    "9:16",
+    "16:9",
+    "1:1",
+    "4:5",
+    "5:4",
+    "3:2",
+    "2:3",
+    "4:3"
+  ],
+  "type": "string"
+}
  2. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/idempotent/non-destructive, so safety is covered. The description adds genuinely new behavioral information: that the call returns a styled prompt stack plus an aspect_ratio, and that the aspect_ratio is meant to be forwarded to generate_image — valuable since there is no output schema.

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?

Front-loaded with what the tool does, followed by the genre menu and the downstream pairing instruction. Some flourish in the opening line ('Put me in a movie') but it is short and every remaining sentence carries operational content.

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?

With no output schema, the description correctly explains what comes back (prompt stack + aspect_ratio) and what to do with it. The only missing piece is sibling differentiation among the many apply_* styling tools, which matters given the crowded namespace.

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%, with the `style` enum descriptions and `aspect_ratio` semantics already detailed in the schema. The description's genre list and the aspect_ratio forwarding note largely restate that. Baseline 3 applies when the schema carries the parameter documentation.

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?

States a specific verb and resource — applies a full cinematic film look to a shot — and enumerates the five genre variants it supports, which map cleanly to the `style` enum. It does not, however, differentiate itself from sibling styling tools like apply_cinematic_anamorphic or apply_style, which an agent must choose between.

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?

Gives a concrete usage path: call this first, then pass the returned aspect_ratio into generate_image. That is clear operative context. It stops short of any exclusionary guidance — it never says when to prefer apply_style or apply_cinematic_anamorphic instead.

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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