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Pritish053

Gemini Image MCP Server

by Pritish053

analyzeImage

Extract objects, text, colors, emotions, or descriptions from base64-encoded images. Choose detail level for tailored analysis results.

Instructions

Analyze images and extract information

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
detailNoLevel of detail for analysis (optional)
imageBase64YesBase64 encoded image data
analysisTypeNoType of analysis to perform (optional)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. 'Analyze' implies a read-only operation, but it does not explain what the tool returns, whether it has side effects, or any operational constraints. This is a significant gap for a tool with no annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise at one sentence with no filler, but it is under-specified. It lacks structure and does not elaborate on the various analysis types or output formats, making it minimally adequate rather than 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 no output schema and no annotations, so the description must explain return values and behavior. It fails to describe the output format or mention the analysisType options, leaving the tool incomplete for effective use. The analysisType enum in the schema partially mitigates this, but the description itself is insufficient.

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 provides 100% coverage with descriptions for all three parameters, including enums for detail and analysisType. The description adds no additional parameter context beyond what the schema already states, so the baseline score of 3 applies.

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 'Analyze images and extract information' clearly identifies the tool's function (analyze) and resource (images), distinguishing it from sibling tools like generateImage and modifyImage. However, 'extract information' is vague and does not specify what information is extracted, limiting clarity.

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. It does not mention any exclusions or specific use cases, offering no context for tool selection.

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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