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Pritish053

Gemini Image MCP Server

by Pritish053

applyStyleTransfer

Apply artistic styles like anime, cyberpunk, or vintage to an image via base64 data. Adjust intensity for subtle to strong effects.

Instructions

Apply artistic styles to existing images

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
styleYesArtistic style to apply
intensityNoStyle intensity from 0 to 100 (optional)
imageBase64YesBase64 encoded image data
Behavior2/5

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

With no annotations provided, the description bears the full burden of behavioral disclosure. It fails to mention whether the operation mutates the input image, returns a new image, or has side effects. No details on image format constraints, size limits, or error conditions are given, so the agent cannot anticipate the tool's behavior beyond the basic function.

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 description is a single concise sentence, front-loaded with the core action. There is no redundancy or fluff, making it efficient. However, it may be too sparse, but for what it says, it is well-structured.

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

Completeness2/5

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

The tool has three parameters (including an enum and base64 input) and lacks both annotations and an output schema. The one-line description does not explain what the tool returns, any constraints, or behavioral nuances, making it insufficient for an agent to use correctly without additional assumptions.

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?

The input schema has 100% coverage, describing all three parameters with clear definitions. The description adds no extra meaning, such as how intensity interacts with style or the base64 encoding contract. Per the rubric, baseline 3 is appropriate because the schema handles parameter documentation, and the description does not contradict or enhance it.

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 clearly states a specific verb+resource: 'Apply artistic styles to existing images.' It implies a transformation operation and distinguishes from generation by specifying 'existing images,' but it does not explicitly differentiate from modifyImage, which could overlap. Thus, it's clear but not fully sibling-differentiated.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like modifyImage or generateImage. It lacks any context about prerequisites, exclusions, or appropriate scenarios, leaving the agent to infer usage from the tool name alone.

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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