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vparsatwar-git

higgsfield-mcp-unified

create_character_tool

Train a reusable Soul character from reference images for consistent AI generation. Input a name and image URLs; results are best-effort until verified.

Instructions

Train a reusable Soul character from reference images. Results best-effort until verified.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
image_urlsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
rawNo
nameYes
statusYes
image_countYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose one real behavioral trait – the training is best-effort and results are unverified until checked – which is useful beyond the schema. It says nothing about long-running/async behavior, whether a job id is returned (despite list_jobs_tool and get_status_tool siblings), auth requirements, or failure modes.

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?

Two short sentences with no filler, and the core action is front-loaded. The caveat sentence is terse and earns its place, though the description is arguably too lean for the gaps it leaves.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-shape explanation is not required. However, for a training tool with two undocumented required parameters, no annotations, and asynchronous siblings in the toolset, the description omits the parameter meaning, workflow prerequisites, and job-tracking context an agent needs to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and there are two required parameters. 'Reference images' loosely maps to image_urls but gives no format, count, or source constraints (e.g., must come from upload_image_tool), and the required 'name' parameter is never explained at all.

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+resource combination ('Train a reusable Soul character from reference images') that is distinguishable from siblings like generate_image_tool or upload_image_tool. It does not explicitly contrast itself with any named sibling, which keeps it short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this versus alternatives such as generate_image_tool (create a one-off image), upload_image_tool (stage a reference image), or preflight_check_tool (validate first). 'Results best-effort until verified' hints at a caveat but never states prerequisites or the intended workflow.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.