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QuickBuild agent tools (x402)

Generate image (FLUX.1 schnell)

generate_image
Read-only

[PAID $0.01 USDC per call via x402 on Base; errors are free] Generate an original 1024x1024 image from a text prompt with FLUX.1 [schnell] on Workers AI (about 2-5 s). Returns JSON with image_base64 + mimeType, or the raw image bytes with format=jpeg. Content policy: no sexual/nude, gore, hate, real or famous people, or ID documents/currency; such prompts get HTTP 400 and are not charged. All params optional: with no prompt a sample watercolor lighthouse is drawn.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stepsNoDiffusion steps, more = more detail (default 4).
promptNoWhat to draw (max 1000 chars). Optional: defaults to a watercolor lighthouse.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Goes well beyond the annotations (readOnlyHint/openWorldHint/idempotentHint/destructiveHint) by disclosing the paid x402/Base pricing model, that failed content-policy calls are not charged, expected latency (2-5 s), the HTTP 400 failure mode, the full content policy, and the two possible response encodings. This is exactly the behavioral context an agent needs before spending money.

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?

Dense but front-loaded: pricing, purpose, output shape, policy, and defaults each arrive in a logical order, and every clause carries usable information. It is a single long block rather than a run-on sentence, but the semicolon-chained style is slightly heavier than necessary.

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

Completeness5/5

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

With no output schema, the description correctly carries the return contract itself (JSON with image_base64 + mimeType, or raw bytes with format=jpeg), plus cost, latency, and policy failure behavior. An agent has everything needed to decide, call, and interpret the result.

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 already 100%, so the schema carries the parameter burden and 3 is the baseline. The description mostly restates schema defaults ('all params optional', the no-prompt lighthouse fallback) rather than adding new syntax or format detail. It does reference a 'format=jpeg' switch that does not exist in the input schema, which is extra information but also a mild inconsistency an agent could trip on.

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+resource (generate an image from a text prompt), names the model and resolution (FLUX.1 [schnell], 1024x1024), and describes the output shape. No sibling tool does image generation, so there is nothing to confuse it with, and the closest neighbor (text_to_speech) is clearly distinct.

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 makes the trigger condition explicit (a text prompt, optional) and clarifies the degenerate case ('with no prompt a sample watercolor lighthouse is drawn'). It also states cost and content-policy gating, which affect whether to call it. It stops short of naming alternatives, but no competing image-generation sibling exists to route away from.

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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