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Make image

make_image

One picture from a description in one call, the still twin of make_video: wires the image model, prepares the render and answers like estimate_run_cost: the price, whether the balance covers it, and a quoteId. It does NOT start the render: tell the person the price, and once they accept, call run_pipeline with the returned pipelineId and quoteId (no inputs), then poll get_run; the picture is outputs.image. Pass referenceImageUrls to change or restyle pictures the account already has ("make this render photo real", "same scene at night"): the model works from them and keeps their composition. A local file goes into the library first with create_upload_url and import_media. Needs the pipelines:write scope; the run needs pipelines:run.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "prompt": "<prompt>"
    },
    "name": "make_image"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameNoWhat to call the render.
modelNoAn image model, only when the person asked for one by name. Defaults to Nano Banana (google/gemini-2.5-flash-image).
promptYesWhat the picture shows, or for a reference, what to change about it.
aspectRatioNoThe picture's shape. Omit it to let the model choose (a square, or the shape of the reference).
maxPriceUsdNoThe most the person will pay for this picture, if they said.
referenceImageUrlsNoUp to 4 pictures in the account's library (from import_media, list_assets or a run's outputs), copied exactly, for the model to work from.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / model / enum
      Previous value: -[
      -  "google/gemini-2.5-flash-image",
      -  "google/gemini-3.1-flash-lite-image",
      -  "google/gemini-3-pro-image",
      -  "black-forest-labs/flux.2-pro",
      -  "bytedance-seed/seedream-4.5",
      -  "bytedance-seed/seedream-5-0-pro",
      -  "recraft/recraft-v4.1",
      -  "openai/gpt-image-2",
      -  "black-forest-labs/flux-3-image",
      -  "bytedance-seed/seedream-5-0-flash",
      -  "tencent/hy-image-v3.5-preview",
      -  "google/gemini-nano-banana-2.1",
      -  "microsoft/mai-image-2.6",
      -  "microsoft/mai-image-2.6-flash",
      -  "bytedance-seed/seedream-5-0-lite",
      -  "sourceful/riverflow-v2.5-fast",
      -  "krea/krea-2-large",
      -  "krea/krea-2-medium",
      -  "krea/krea-2-medium-turbo",
      -  "black-forest-labs/flux-3-image-klein",
      -  "qwen/qwen-image-2.1-pro",
      -  "qwen/qwen-image-2.1-turbo"
      -]New value: +[
      +  "google/gemini-2.5-flash-image",
      +  "google/gemini-3.1-flash-lite-image",
      +  "google/gemini-3-pro-image",
      +  "black-forest-labs/flux.2-pro",
      +  "bytedance-seed/seedream-4.5",
      +  "bytedance-seed/seedream-5-0-pro",
      +  "recraft/recraft-v4.1",
      +  "openai/gpt-image-2",
      +  "black-forest-labs/flux-3-image",
      +  "bytedance-seed/seedream-5-0-flash",
      +  "tencent/hy-image-v3.5-preview",
      +  "google/gemini-nano-banana-2.1",
      +  "microsoft/mai-image-2.6",
      +  "microsoft/mai-image-2.6-flash",
      +  "bytedance-seed/seedream-5-0-lite",
      +  "sourceful/riverflow-v2.5-fast",
      +  "krea/krea-2-large",
      +  "krea/krea-2-medium",
      +  "krea/krea-2-medium-turbo",
      +  "black-forest-labs/flux-3-image-klein",
      +  "qwen/qwen-image-2.1-pro",
      +  "qwen/qwen-image-2.1-turbo",
      +  "openai/gpt-image-2.6-flare"
      +]
  2. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations only say it is a non-destructive, non-idempotent write; the description carries far more: it is a two-phase quote-only call, what the quote contains (price, balance coverage, quoteId), where the finished artifact appears (outputs.image), and the exact scopes required (pipelines:write to prepare, pipelines:run to execute). That is behavior beyond anything structured fields disclose.

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?

The most decision-relevant facts (one image, does not start the render) are front-loaded, and nearly every clause carries operational information. It is dense and colon-chained, with a slightly tangled "answers like estimate_run_cost" construction, but there is little outright filler.

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?

There is no output schema, so the description must explain what comes back, and it does: price, balance sufficiency, quoteId, pipelineId, and outputs.image after the run. Combined with the scope requirements and prerequisite routing, an agent has everything needed to drive this tool through its full two-step lifecycle.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, and the description still adds meaning the schema does not: use referenceImageUrls only to restyle existing library pictures ("make this render photo real") with composition preserved, and specify model only when the person names one. It does not add much on maxPriceUsd or aspectRatio beyond the schema text.

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?

"One picture from a description in one call" states a specific verb and resource, then distinguishes itself from two siblings by name: it is "the still twin of make_video" and "answers like estimate_run_cost." An agent can tell this apart from make_video and run_pipeline 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?

Explicit when-not guidance ("It does NOT start the render") and an ordered alternative path: quote first, tell the person the price, then run_pipeline with the returned pipelineId and quoteId, then poll get_run. It also routes prerequisites to the right siblings (create_upload_url and import_media for local files) and explains the referenceImageUrls use case with concrete phrasing examples.

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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