Skip to main content
Glama

Generate or edit an image

generate_image

Create or edit images with a Modelflare image model, then save the result to the output directory. Usage is billed to your Modelflare balance by actual usage.

Instructions

Generates an image, or edits one with edit=true, using a Modelflare image model, and saves the result to the output directory. Billed to the Modelflare balance by actual usage.

Input Schema

NameRequiredDescriptionDefault
editNoUse the edits route (OpenAI-compatible image models only).
modelYesImage model ID from list_models.
promptYes
parametersNoModel-specific request fields, sent unchanged. Read the model's docs page (from list_models) for the exact fields.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior4/5

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

With only openWorldHint provided, the description carries the behavioral burden and adds real value: it discloses that the result is written to an output directory and that the call is billed to the Modelflare balance by actual usage. It does not cover authentication/permission needs or failure behavior, but the cost and side-effect disclosure is substantive.

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 compact clauses, front-loaded with the core action before the billing note, with no filler. The edit-mode distinction is placed early where it is most actionable.

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 4-parameter tool with a nested passthrough object and no output schema, the description usefully states where output lands and how billing works, covering the main gap left by the missing return schema. It does not warn about model-specific field requirements in the nested parameters object, but the schema covers that.

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 75%, so most parameters are already documented; the description only reinforces edit=true and the list_models source for model. It adds no meaning for prompt or the nested parameters passthrough object, so it does not compensate beyond the schema baseline.

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?

The description names a specific verb+resource (generates/edits an image) and splits the two modes via the edit=true flag, which is precise enough to act on. It does not explicitly contrast with siblings like create_video, but the resource is distinct enough that confusion is unlikely.

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

Usage Guidelines3/5

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

It states that edit=true switches to the edit route and that the model ID comes from list_models, implying a prerequisite lookup. However there is no explicit when-to-use/when-not guidance, no mention of the create_video sibling, and no conditions under which generation versus editing should be preferred beyond the boolean flag.

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