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generate_image

Generate an image from a text prompt only (scenes, backgrounds, product shots). Do NOT use this for putting avatars on hooks - use face_swap instead. Costs 5 credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoImage model
promptYesImage generation prompt
resolutionNoOutput resolution
aspectRatioNoAspect ratio
referenceImageUrlNoReference image URL for variations

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses cost (5 credits) and an input constraint, but omits whether generation is synchronous or async — a meaningful gap given the sibling get_render_status implies polling-style rendering — and says nothing about output location or failure behavior.

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?

Three short clauses, each earning its place: scope, exclusion/alternative, and cost. The most decision-relevant routing info (what it is and what it isn't) is front-loaded.

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?

For a 5-param generation tool with no annotations and no output schema, the description covers selection and cost but leaves return behavior and sync/async semantics unexplained despite a get_render_status sibling hinting at async rendering. Adequate but with clear gaps.

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 description coverage is 100% with 3 enums, so the schema already documents model, resolution, aspect ratio, and referenceImageUrl. The description adds no parameter-level detail, so the baseline 3 applies. Mild tension: 'text prompt only' while referenceImageUrl exists for variations.

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 an image') plus a clear scope constraint ('from a text prompt only') with example use cases (scenes, backgrounds, product shots). It explicitly names the sibling it is not for (face_swap for avatar-on-hook), so an agent can distinguish it without opening any schema.

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

Usage Guidelines5/5

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

Gives an explicit when-not rule ('Do NOT use this for putting avatars on hooks') and routes the agent to the correct alternative tool by name ('use face_swap instead'). This is the strongest form of usage guidance — condition plus 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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