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vparsatwar-git

higgsfield-mcp-unified

generate_batch_tool

Submit multiple AI image or video generation requests in one batch to Higgsfield models. Each request includes a model ID, prompt, and optional parameters.

Instructions

Submit multiple generations at once. Each request: {kind, model_id, prompt, ...params}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
resultsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. It says 'submit' but not whether this is asynchronous (job IDs, list_jobs/get_status siblings suggest it likely is), what happens on partial failure, or any auth/rate-limit constraints. Only bare minimum is conveyed.

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?

Two short sentences, front-loaded with the action and followed by the per-item shape. Nothing wasteful.

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

Completeness3/5

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

An output schema exists, so return values need not be described. Still, for a batch mutation with no annotations and a single opaque array parameter, the description omits partial-failure behavior, whether batches are homogeneous, and sync/async expectations.

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 0% and the schema only declares an untyped array of free-form objects, so the description's '{kind, model_id, prompt, ...params}' is a genuine value add. However, the '...params' tail is vague and the semantics of 'kind' (which values map to which generation type) are not explained.

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 resource: submit multiple generations at once. This distinguishes it from the single-generation siblings (generate_image_tool, generate_video_tool) by the word 'multiple', but it never names those siblings or clarifies the batch-versus-single split explicitly.

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 choose batch submission over individual generation calls, no note on ordering, limits, or whether mixing kinds in one batch is allowed. The agent is left to infer usage entirely.

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