Skip to main content
Glama
xiaobenyang-com

Extract-Image

extract_image_from_file

extract_image_from_file

Extract images from local files for visual analysis, OCR text extraction, and object recognition in screenshots, photos, diagrams, and documents.

Instructions

Extract and analyze images from local file paths. Supports visual content understanding, OCR text extraction, and object recognition for screenshots, photos, diagrams, and documents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYes
resizeNo
max_widthNo
max_heightNo
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. It mentions capabilities like OCR and object recognition, but lacks details on behavioral traits such as performance limits, error handling, supported image formats, or output structure. This leaves significant gaps for a tool with multiple parameters and no output schema.

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 appropriately sized with two sentences that are front-loaded with key information. Each sentence adds value: the first states the purpose and scope, and the second lists capabilities and supported file types, with no wasted words.

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?

Given the complexity (4 parameters, 0% schema coverage, no output schema, no annotations), the description is incomplete. It covers purpose and capabilities but misses critical details like parameter explanations, behavioral constraints, and output format, making it inadequate for effective tool selection and invocation.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It doesn't explain any parameters (file_path, resize, max_width, max_height) beyond what the schema provides (e.g., types and required status). No additional meaning or usage context is given for parameters, failing to address the coverage gap.

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 the verb ('extract and analyze') and resource ('images from local file paths'), and distinguishes it from siblings by specifying 'local file paths' (vs. base64 or URL sources). However, it doesn't explicitly name the sibling tools for comparison, keeping it at 4 rather than 5.

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

Usage Guidelines3/5

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

The description implies usage context by listing supported file types ('screenshots, photos, diagrams, and documents') and capabilities ('visual content understanding, OCR text extraction, and object recognition'), but it doesn't explicitly state when to use this tool versus the sibling tools (extract_image_from_base64, extract_image_from_url) or any exclusions.

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/xiaobenyang-com/1777316659462147'

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