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Follow subject

follow_subject

Keep the person in frame where the frame crops the footage, such as 16:9 shots on a 9:16 canvas: the clip fills the frame and its x/y are keyframed to follow the subject (from the subject matte, made first if needed, about a minute for a 15 s clip). Run it after changing the format, then check with render_frame.

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": {
      "clipIds": "<clipIds>"
    },
    "name": "follow_subject"
  }
}

Input Schema

NameRequiredDescriptionDefault
clipIdsYes
projectIdNoProject to act on (default: the open one)
approvalIdNoOnly after needs_approval: the id it gave, once the user said yes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare this is a non-read-only, non-destructive, closed-world mutation, so the safety profile is covered. The description adds real value beyond that: it discloses the ~1 minute runtime for a 15 s clip and that a subject matte is created first if needed, an implicit side effect. It does not describe failure modes or what happens to existing keyframes.

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 the core effect, then the concrete use case, then the operational notes. Dense but every clause carries information; the parenthetical about matte creation and timing is slightly buried but not wasteful.

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?

For a mutation tool with no output schema, the description covers purpose, prerequisite (format change), implicit side effect (matte creation), cost (about a minute), and verification (render_frame). The approval flow is only implied through the approvalId parameter, which is a minor gap.

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 67%, with projectId and approvalId already documented in the schema. The description adds no meaning to clipIds beyond the singular 'the clip', and does not clarify whether multiple clips are processed independently or as a group. Baseline 3 is appropriate given the schema does most of the work.

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 effect: keep the subject in frame by keyframing the clip's x/y from a subject matte, with the concrete case of 16:9 footage on a 9:16 canvas. This is clearly distinct from siblings like punch_in or text_behind_subject, though it never names an alternative explicitly.

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 explicit sequencing ('Run it after changing the format') and a verification step ('check with render_frame'), which tells the agent both when to invoke it and how to confirm success. It stops short of stating when not to use it or what to do if the matte fails.

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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