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by ai.uwear
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Create Video Montage

propose_montage

ONLY for video montage/stitching/export workflows. Use when the user explicitly asks to create a montage, stitch clips, make a reel, export a video sequence, make video clips from images, or combine images/videos into one final video. Never use this for a photoshoot, lookbook, product shoot, collection shoot, outfit shoot, garment shoot, or image-generation request; those must use request_user_context followed by propose_brief/update_brief. Do not call this merely because selected context contains images, generations, garments, or models. A photoshoot may later feed a montage, but the photoshoot itself must be proposed as a BriefProposal first. PROPOSES the montage for user review — user can edit clips, generate missing videos, then export. Supports: existing videos with optional trim (target_duration or start_time/end_time), images that need video generation (specify video_model + a bespoke per-image motion prompt, and optionally target_duration or duration), per-clip speed/mute, global aspect ratio. If the user asks for clips to be e.g. '3 seconds each', set target_duration: 3 on every item, including image items. For image items, avoid generic repeated prompts: tailor each prompt to the specific image and any requested zoom, movement, energy, or camera direction. If motion is not specified, inspect the image first with view_image and then write a fitting motion prompt from the image content before proposing. The user reviews and confirms in the UI. Export is free (0 credits); video generation clips cost credits per their model. Prefer create_montage / edit_montage for a saved montage the user can open in Uwear.

Input Schema

NameRequiredDescriptionDefault
itemsYesOrdered list of montage items. Each is either an existing video or an image needing video generation. Min 1, max 10.
board_idNoThe open Shoot Board's board_id, from Open Shoot Board or your context.
aspect_ratioNoOutput aspect ratio (e.g. '9:16', '16:9', '1:1')9:16
base_resolutionNoLong edge of the output in pixels; 1920 for a 1080x1920 reel.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / base_resolution / description
      Previous value: -"Output resolution height in pixels"New value: +"Long edge of the output in pixels; 1920 for a 1080x1920 reel."
  2. Changed1 schema field changed
    • addedInput schema / properties / board_id
      Added value: +{
+  "description": "The open Shoot Board's board_id, from Open Shoot Board or your context.",
+  "type": "string"
+}
  3. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations only say it is a non-read-only, non-destructive, non-idempotent call; the description adds genuinely new behavior: it PROPOSES for user review rather than executing, the user can edit clips and generate missing videos in the UI, and export is free while image-to-video clips cost credits per model. It does not describe failure modes or what happens to an existing pending proposal, which keeps it off a 5.

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?

Routing rules are front-loaded before any schema detail, which is the right order. It is long and repeats the exclusion idea ('Never use this for...' and 'Do not call this merely because selected context contains images...'), but nearly every sentence carries a decision or a constraint, so it avoids true bloat.

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?

No output schema exists, and the description compensates by explaining that the result is a reviewable proposal with editing, clip generation, and export steps, plus credit implications. For a 4-parameter, credit-consuming workflow tool, an agent has everything needed to call it or route elsewhere.

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 100%, so baseline is 3; the description earns above that by translating intent into parameter values ('3 seconds each' → target_duration: 3 on every item including image items) and by prescribing per-item prompt quality and the view_image inspection step before writing a motion prompt. It does not cover aspect_ratio/base_resolution choice, but the schema already does.

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 ('PROPOSES') and resource ('montage') plus scope ('video montage/stitching/export workflows'), and explicitly carves out the neighboring territory handled by propose_brief/update_brief. An agent can distinguish this from create_montage, edit_montage, and propose_brief without opening any schema.

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 triggers (create a montage, stitch clips, make a reel, export a sequence, make clips from images), explicit when-NOT-to-use cases (photoshoot/lookbook/product/outfit shoots and image generation), and names the alternative path (request_user_context then propose_brief/update_brief). It even handles the ambiguous case where a photoshoot later feeds a montage.

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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