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studio.suggest_social_clips

Find the best short-form moments in a long studio video and return them as ranges with a title, a hook line, a one-sentence rationale and measured evidence (captioned words, words per second, whether it starts on a scene cut). It creates and changes nothing. To make a suggestion into a project, call studio.create_social_clip with its start_ms and end_ms; then render that project with video.export_create and the same preset. Pass count (1 to 10), target_preset (default shorts_9x16; it sets the shape and the longest length, never over 60 s) and optionally asset_id to use only the scenes cut from one uploaded video. Costs up to about $0.0012 per call for the model; the wallet is checked first and an unfunded wallet gets PAYMENT_REQUIRED with nothing charged. Refuses, with nothing charged: a project with no finished footage (COLD_START: add footage with studio.add_scene_from_asset or studio.generate_scene), an asset_id that is not a video or not on the timeline yet (place it with studio.add_scene_from_asset), footage shorter than 5 s, read-only tokens and viewer roles. A pick outside the real footage is dropped with its reason in 'dropped', never stretched to fit.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "project_id": "<project_id>"
    },
    "name": "studio.suggest_social_clips"
  }
}

Input Schema

NameRequiredDescriptionDefault
countNoHow many suggestions to return, 1 to 10 (default 3). Fewer can come back when the video has fewer distinct moments.
focusNoOptional: what to look for, such as 'the product demo'. It only ranks moments; it is never treated as an instruction.
asset_idNoOptional: suggest only from the scenes cut from this video asset (vas_...). studio.get_composition lists the assets; the asset must already be on the timeline (studio.add_scene_from_asset places it).
project_idYesThe studio project (vp_...) holding the long video. studio_project_list shows your projects.
target_presetNoThe export preset the shorts are for (default shorts_9x16). It sets the shape and the longest allowed length; pass the same preset to studio.create_social_clip and video.export_create.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Discloses cost (~$0.0012), the wallet pre-check and PAYMENT_REQUIRED with nothing charged, plus named refusal conditions (COLD_START, non-video asset_id, footage under 5 s, read-only tokens, viewer roles) and the fact that out-of-range picks are dropped with a reason rather than stretched. The one unexplained point is that it claims to 'create and change nothing' while the annotation sets readOnlyHint=false; that is reconcilable as a billing side effect, but the description never says so.

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 purpose and non-mutating guarantee are front-loaded, and nearly every clause carries operative information (cost, refusals, handoff, dropped picks). It is a dense single block rather than a structured list, which makes the refusal and cost details harder to scan than they need to be.

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?

With no output schema, the description carries the return-shape burden itself and does so: ranges, title, hook, rationale, measured evidence, and the 'dropped' array with reasons. Combined with cost, refusal codes and the downstream handoff, an agent has everything needed to invoke and interpret the result.

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%, so the baseline is 3 and the schema already documents all five parameters including defaults and bounds. The description adds real meaning for target_preset ('sets the shape and the longest length, never over 60 s' and must be reused downstream) and asset_id scope, but says nothing about 'focus' and only restates count, so the increment over the schema is modest.

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 ('find the best short-form moments in a long studio video') plus the exact return shape: ranges with title, hook, rationale and measured evidence. It explicitly distinguishes itself from the downstream sibling studio.create_social_clip, so an agent can tell suggestion from creation without opening a 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 the full when-to-use chain: call this, then studio.create_social_clip with the returned start_ms/end_ms, then video.export_create with the same preset. It also names concrete alternatives for error paths (studio.add_scene_from_asset, studio.generate_scene, studio.get_composition), so every routing decision is pre-answered.

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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