Sibyl

generate_image

Generate an image from a text prompt, saving the output as a PNG. Transform written descriptions into visual content with Google's Gemini model.

Instructions

Generate an image from a text prompt with Gemini (Nano Banana). Saves to output_path.

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>",
      "output_path": "<output_path>"
    },
    "name": "generate_image"
  }
}

Input Schema

Name	Required	Description
`model`	No
`prompt`	Yes
`output_path`	Yes	Where to save the image (.png).

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 7, 2026

TDQS

A3.6/5.0

Behavior3/5

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

No annotations are provided, so the description carries the transparency burden. It discloses a key side effect ('Saves to output_path') and the model used, but it does not explain whether existing files are overwritten, what the function returns, or any error conditions. This adds some context but leaves significant behavioral details undisclosed.

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?

The description is extremely concise: two short sentences, no wasted words. The main action and key side effect are front-loaded. Every word earns its place.

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 tool with no output schema and no annotations, the description is minimal but covers the core action and output location. However, it is missing important information for reliable invocation, such as return behavior, file handling (overwrite vs. error), and any model constraints. This is adequate for a simple tool but has clear gaps.

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

Parameters2/5

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

Schema coverage is only 33% (only output_path has a description). The description mentions prompt implicitly ('text prompt') and output_path explicitly, but it does not clarify the 'model' parameter at all. It says 'with Gemini (Nano Banana)', which may suggest a fixed model, leaving the role of the model parameter ambiguous. The description fails to compensate for the low schema coverage.

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?

The description clearly states the tool's function: 'Generate an image from a text prompt' with a specific model ('Gemini (Nano Banana)') and the save location. This is a specific verb+resource pairing that distinguishes it from siblings like edit_image and generate_video.

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?

The description implies usage: use this when you need to create an image from a text prompt and save it to a file. However, it does not explicitly mention when to prefer this over 'edit_image' or 'generate', nor does it provide any exclusions or alternative guidance.

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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