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set_scene_image

Put the user's own picture on one scene of a finished multi scene or whiteboard video. Free and unlimited. Needs a public https link straight to a JPG, PNG or WebP file (up to 12 MB); pictures pasted into the chat cannot reach this tool. Like regenerate_scene_image, it is in the video only after update_video. Only use a picture the user has asked you to use.

Input Schema

NameRequiredDescriptionDefault
sceneYesScene number from list_video_scenes.
video_idYes
image_urlYesPublic https link to the image file.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses cost ('Free and unlimited'), input constraints (public HTTPS URL, JPG/PNG/WebP, up to 12 MB), a consent rule, and the crucial fact that the change is not live until update_video runs. It stops short of saying whether the existing scene image is replaced, whether failures are recoverable, or what the call returns.

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?

Front-loaded with the action and scope, then layered with constraints in descending order of importance. Every clause carries a distinct operational fact — cost, input format, outcome timing, consent — with no padding.

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?

For a 3-parameter mutation tool with no annotations and no output schema, the description covers prerequisites, input restrictions, the two-step commit requirement, and a safety constraint. What an agent needs in order to call this correctly is present.

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 67%, and the description compensates by pinning down image_url format constraints (public HTTPS, JPG/PNG/WebP, 12 MB limit) that go well beyond the terse schema text, and by pointing scene numbering at list_video_scenes. video_id remains entirely undocumented in both places, which keeps this below the top score.

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?

States a specific verb and resource ('Put the user's own picture on one scene') plus the scope of videos it applies to (finished multi-scene or whiteboard). It explicitly names regenerate_scene_image as the neighboring alternative, so an agent can distinguish it without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit when-to-use conditions (finished video, one scene, user-supplied picture) and when-not conditions (chat-pasted images cannot reach this tool, only use a picture the user has asked for). It also names the necessary follow-up step, update_video, and the sibling it complements, regenerate_scene_image.

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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