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create_character_v3

Create pixel art characters from a text description or rotate a provided reference image. Returns a character ID.

Instructions

Create a character using the v3 model. Two modes: provide a south-facing reference_image to rotate that exact character, or omit it to generate from scratch via description. Output 32-256px (advisory in reference mode). Returns a character_id. The newest character generator — prefer over create_character_4dir/8dir for best quality.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoDisplay name (defaults to first 50 chars of description)
seedNoSeed for deterministic generation (default 0)
viewNoCamera view angle (default 'low top-down')
detailNoDetail level hint for from-scratch mode (default 'medium detail')
outlineNoOutline style hint for from-scratch mode (default 'single color black outline')
image_sizeNoOutput frame size, 32-256px (advisory in reference mode)
descriptionYesCharacter description (used as prompt + display name)
template_idNoBody type for skeleton reconstruction (default 'mannequin')
no_backgroundNoGenerate with transparent background
enhance_promptNoAuto-expand the description into a richer prompt before generating (default false)
reference_imageNoSouth-facing reference image; if provided, v3 rotates this exact character
Behavior3/5

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

With no annotations provided, the description carries full burden. It adequately describes the two operational modes and output constraints (advisory size in reference mode, returns character_id). However, it lacks details on potential side effects, permissions, or processing time, which is a moderate gap.

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?

The description is concise (3 sentences) and well-structured, with the main purpose front-loaded. Every sentence adds value, and there is no redundancy.

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?

Given tool complexity (11 params, nested objects, two modes), the description covers the core behavior and mode distinction. It lacks error handling or authentication details, but for a character creation tool, it is largely complete. A minor gap in mentioning possible issues or return format beyond character_id.

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 baseline is 3. The description adds context beyond the schema by explaining the two modes and that image_size is advisory in reference mode, but does not elaborate on other parameters. This meets the minimum for a well-documented 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?

The description clearly states the tool creates a character using the v3 model, identifies two distinct modes (reference image or from scratch), and explicitly distinguishes it from sibling tools create_character_4dir/8dir by recommending v3 for best quality.

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?

The description provides guidance on when to use this tool (prefer over older character generators) and explains the two modes with conditions for each. However, it does not include when-not-to-use scenarios or alternative tools beyond the two mentioned.

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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