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JaviGala

web-perception-mcp

by JaviGala

analyze_image

Analyze local image files with vision AI. Submit a prompt to extract visual elements, layout, colors, or content from screenshots, mockups, or design files. Supports multiple image formats.

Instructions

Analyze one or more local image files using MiniMax vision. No browser involved. Use for screenshots, mockups, design files, or any image. Supports PNG, JPEG, GIF, WebP, BMP.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
image_pathYesPath to a single image file, or an array of paths for multi-image analysis (e.g. before/after comparison). Absolute or relative paths accepted.
promptYesThe question or instruction for analyzing the image(s). Be specific about what visual elements, layout, colors, or content you want extracted.
response_formatNoOptional. Set to 'json_object' to get structured JSON output. Default is 'text'.
temperatureNoOptional. Controls randomness (0-2). Lower = more consistent. Default: 0.3.
max_tokensNoOptional. Maximum tokens in the response. Default: 2000.
Behavior2/5

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

With no annotations, the description carries full burden but only states it analyzes images and supported formats. It does not disclose whether the tool is read-only, destructive, or any side effects, rate limits, or authentication needs.

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. Every sentence adds value.

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 the 5 parameters (2 required) and no output schema, the description adequately covers the tool's purpose, when to use, supported formats, and key constraints (local files, no browser). Does not explain return values but that is acceptable without output schema.

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?

Schema coverage is 100% so parameters are already well-documented. The description adds minor value by listing supported file formats, but does not explain parameter semantics further beyond what the schema provides.

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 analyzes local image files using MiniMax vision, specifies no browser involvement, and lists use cases (screenshots, mockups, etc.), distinguishing it from sibling page-related tools.

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

Usage Guidelines4/5

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

The description explicitly says to use for screenshots/mockups/any image and notes 'No browser involved', implying when to use vs page-analysis siblings, but does not explicitly state when not to use or list alternative tools.

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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