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Analyze Image

analyze_image

Extract text-based information from one or more images using Gemini's multimodal analysis. Returns a text summary without generating images.

Instructions

Analyze and extract information from one or more images using Gemini multimodal understanding. Returns a text analysis — no image is generated. Default model: gemini-3-pro-preview.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imagesYesOne or more images to analyze
promptYesWhat to analyze or extract from the image(s)
modelNoModel to use (default: gemini-3-pro-preview)
max_tokensNoMaximum tokens in response (default 16384, up to 64K output limit)
global_media_resolutionNoGlobal image quality for cost optimization. MEDIUM recommended for PDFs (50% savings).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYes
successYes
Behavior3/5

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

Without annotations, the description carries the burden. It discloses key traits: returns text only, default model, and multimodal understanding. However, it omits details like error handling, size limits, or idempotency.

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?

Two sentences, no wasted words. Front-loaded with the core purpose, followed by a key behavioral note and default model. Highly efficient.

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

Completeness4/5

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

Given 5 parameters, an output schema, and no annotations, the description covers the essential purpose and a behavioral trait. It lacks sibling differentiation and usage context, but otherwise meets needs for a moderately complex tool.

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?

Input schema coverage is 100% with detailed descriptions for all parameters. The tool description adds minimal extra meaning beyond restating the default model, so baseline 3 is appropriate.

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?

Description clearly states the tool analyzes and extracts information from images and returns text. It distinguishes from image generation tools by stating 'no image is generated,' but does not explicitly differentiate from similar analysis tools like describe_image or extract_structured_data.

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?

No guidance on when to use this tool versus alternatives. The description does not mention scenarios or limitations, leaving the agent to infer usage without explicit directions.

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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