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create_character

Create a reusable character for the user's videos and save it to their Digital Maker account, from a written description. (A character is placed INTO the scene pictures. For a talking on-screen host, an AI presenter or avatar, use draw_presenter instead.) Every character is made the same way: a FULL BODY figure, head to feet, standing on a plain white background, so it can be dropped into any scene. Once saved, pass its name to create_video and that same character appears in every scene. It also lands in the user's image library. Users keep up to 10.

IF THE USER SHARES A REFERENCE IMAGE (a screenshot of a channel they like, a style they want): look at it yourself and write your own description of the KIND of character it is, then pass that. Describe the archetype, art style, colour palette, build, hair, clothing and general vibe. Ignore the framing and background of what they shared, since the result is always a full-body figure on white regardless. Do NOT try to reproduce a specific individual's face, and do not describe a real identifiable person. The point is a character of a similar style that belongs to this user, not a copy of someone else's.

Costs one image from the user's monthly allowance. Show them the result and offer to redo it before they build a video around it. Available on any plan that includes images, which is Pro and above, even though faceless video itself needs Premium: a Pro user can build their character library now and use it after upgrading.

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": {
      "name": "<name>",
      "description": "<description>"
    },
    "name": "create_character"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYesShort name the user will refer to the character by, e.g. Maya. Must be unique among their characters.
styleNoThe visual world this character belongs to. Use the SAME value you will later pass as style_preset on create_video, so the character matches its own video. When the user shares a reference image, pick the preset whose look matches it: flat 2D illustration is animated_cartoon; dark moody photoreal lit by a single rim light is motivational_dark; gold, marble and wealth imagery is finance_luxury; candlelit period detail is history_ancient; cosmic and nebula lighting is space_scifi; soft neutral tones with lots of negative space is minimalist_clean; ordinary present-day photography is cinematic_documentary. Defaults to cinematic_documentary.
descriptionYesFull visual description: age range, build, hair, clothing, colour palette, art style, expression, overall vibe. The richer this is, the more consistent the character stays across scenes. Avoid naming real people.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations supplied, the description carries the full burden and does so well: it discloses the per-call cost (one image from the monthly allowance), the storage side effect (lands in the image library), the hard quota (10 characters), the invariant output format, and plan eligibility including the Pro-now/Premium-later nuance. It does not describe latency, failure/retry behaviour, or what happens on a duplicate name beyond the schema's uniqueness note.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded in the first sentence, but the five-paragraph block repeats the full-body-on-white invariant twice and restates the plan-eligibility caveat at length. Most sentences earn their place, yet the length is disproportionate for a three-parameter creation tool and would benefit from tighter grouping.

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 zero annotations and no output schema, this covers cost, quota, storage effects, eligibility, and the downstream handoff to create_video, so an agent can call it and set expectations. Remaining gaps are failure handling and how the created character relates to sibling mutation tools (change_character, manage_character).

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% and the enum values are already annotated at length, so the schema does most of the work and the baseline of 3 applies. The description adds real meaning for the description parameter by telling the agent how to translate a user's reference image into words (describe archetype, style, palette, build; ignore framing and background; never describe a real identifiable person).

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?

Opens with a specific verb+resource+destination: creates a reusable character and saves it to the user's Digital Maker account. It pins down the artifact precisely (full-body figure, head to feet, plain white background) and separates itself from draw_presenter in a parenthetical. It does not distinguish itself from other close siblings such as draw_character, save_character or create_3d_character, which leaves some ambiguity in a crowded namespace.

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?

Explicit routing guidance against one sibling (talking host/avatar -> draw_presenter) and a clear post-creation workflow (show the result, offer a redo, then pass the name to create_video). The reference-image paragraph is genuinely useful when-to guidance for a common ambiguous input. It lacks the same explicit routing against draw_character/save_character/manage_character, so it falls short of a 5.

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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