Skip to main content
Glama
seepine
by seepine

understand_image

Analyze images by providing a text prompt to extract descriptions, details, or information from local files or URLs. Supports JPEG, PNG, and WebP.

Instructions

You MUST use this tool whenever you need to analyze, describe, or extract information from an image.

An LLM-powered vision tool that can analyze and interpret image content from local files or URLs based on your instructions. Only JPEG, PNG, and WebP formats are supported.

Args: prompt (str): A text prompt describing what you want to analyze or extract from the image. image_source (str): The location of the image to analyze. - HTTP/HTTPS URL: "https://example.com/image.jpg" - Local file path (relative or absolute) - If path starts with @, strip the @ prefix before passing

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesA text prompt describing what you want to analyze or extract from the image.
image_sourceYesThe location of the image to analyze (URL or local file path).
Behavior4/5

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. It adds important constraints: supports only JPEG/PNG/WebP, explains the @ prefix stripping for image_source, and discloses that it's LLM-powered. It does not describe return format or side effects, but for a read-only analysis tool these are less critical.

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 compact and well-structured. It front-loads a clear usage directive, then provides a capability statement, format constraint, and parameter details. Every sentence contributes useful information without unnecessary fluff.

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?

The tool is simple with only two parameters and no output schema. The description adequately covers purpose, usage, and input constraints. However, it does not explicitly state what the tool returns (e.g., a text description or analysis result), which is a notable gap given the absence of an output schema.

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

Parameters4/5

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

The schema covers both parameters at 100%, so the baseline is 3. The description adds value by detailing the allowed forms of image_source (URL, local path) and the @ prefix rule, which is not present in the schema. This additional context justifies a 4.

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 purpose with specific verbs ('analyze, describe, or extract information') and identifies the resource (image). It distinguishes itself from the sibling tool 'web_search' by focusing exclusively on image content interpretation.

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 'You MUST use this tool whenever you need to analyze, describe, or extract information from an image,' providing clear trigger conditions. However, it does not mention explicit when-not-to-use cases or alternatives beyond the implied contrast with web_search.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/seepine/minimax-coding-plan-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server