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xiaobenyang-com

Extract-Image

extract_image_from_url

extract_image_from_url

Extract images from web URLs for visual content analysis and text extraction. Convert images to base64 format suitable for LLM processing.

Instructions

Extract and analyze images from web URLs. Perfect for analyzing web screenshots, online photos, diagrams, or any image accessible via HTTP/HTTPS for visual content analysis and text extraction.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
resizeNo
max_widthNo
max_heightNo
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions analysis and text extraction, but lacks details on behavioral traits such as error handling (e.g., invalid URLs, unsupported formats), performance (e.g., timeouts, rate limits), or output format (e.g., what analysis results include). This is a significant gap for a tool with no annotation coverage.

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 and front-loaded, with the core purpose stated first. Both sentences add value, but it could be slightly more concise by integrating the use cases more tightly with the main purpose.

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 annotations, no output schema), the description is incomplete. It lacks details on parameter usage, behavioral traits, and output expectations, 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 mentions extracting from URLs but does not explain the purpose or usage of parameters like 'resize', 'max_width', or 'max_height'. The description adds minimal value beyond what the schema provides, failing to address the coverage gap.

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 ('extract and analyze') and resources ('images from web URLs'), and distinguishes it from siblings by specifying the input source (URLs vs. base64 or file inputs). It also lists concrete use cases like analyzing screenshots, photos, and diagrams.

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 provides clear context for when to use this tool (for images accessible via HTTP/HTTPS, for visual content analysis and text extraction), but does not explicitly state when not to use it or name alternatives. The sibling tool names imply usage based on input source, but no explicit guidance is given.

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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