CutClip.one

character.generate_sheet

Generate the character map (front, ¾ left/right, profile, back, full body, close-up) with an image model, keeping one identity. With no reference yet, a front portrait is generated first from the description. Costs credits per image (see generation.list_models), charged to the project owner. Runs in the background — poll generation.list. Views the character already has are skipped unless listed in views.

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": {
      "projectId": "<projectId>",
      "characterId": "<characterId>"
    },
    "name": "character.generate_sheet"
  }
}

Input Schema

Name	Required	Description
`label`	No	Free-text pose/expression for a custom or expression view
`views`	No
`projectId`	Yes
`imageModel`	No
`characterId`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 6, 2026

TDQS

A4.7/5.0

Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses credit cost per image charged to the project owner, that execution is asynchronous and requires polling generation.list, and that already-existing views are skipped rather than overwritten. These are exactly the operational traits an agent needs before invoking a paid, long-running mutation.

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?

Four tight sentences, front-loaded with what is produced, then the no-reference fallback, then cost, then async/skip semantics. No filler and no repetition of the schema.

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 an async, credit-consuming generation tool with no output schema, the description covers the essentials: what gets produced, cost source, polling target, and skip behavior. Nothing critical to a correct invocation is missing.

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 only 20% (only label is documented), so the description must compensate, and it does for the two non-obvious parameters: views is explained as an override of the skip-existing behavior, and imageModel is tied to generation.list_models. projectId and characterId are self-evident, but label's role in custom/expression views is left to the schema.

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 ('Generate the character map') and enumerates the exact view set produced (front, ¾ left/right, profile, back, full body, close-up), plus the identity-consistency constraint. This clearly separates it from the sibling character.generate_view, which handles a single view.

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 concrete when-to-use context: with no reference yet a front portrait is generated first, and existing views are skipped unless explicitly listed in views. It also routes the agent to generation.list_models for cost and generation.list for polling. It stops short of explicitly naming character.generate_view as the single-view alternative.

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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