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rnd-pro
by rnd-pro

extract_virtual_canvas

Extract structured data from virtual canvas elements instead of taking a screenshot. Optionally wait for a CSS selector and include non-interactive elements for more complete extraction.

Instructions

Extract virtual canvas data from current page instead of taking screenshot

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoURL to navigate to (optional if page already loaded)
wait_forNoCSS selector to wait for before extraction (optional)
include_non_interactiveNoInclude non-interactive elements in extraction
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It fails to mention whether navigation occurs, potential side effects, permissions, or the format of the returned data. This is a significant gap for a tool with optional parameters like url and wait_for.

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 a single sentence that starts with the action verb and contains no filler. Every word contributes meaning, making it highly concise and well-structured.

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 no output schema and no annotations, the description is insufficiently complete. It does not explain what 'virtual canvas data' includes, how the extraction works, or what the agent should expect as a result. The minimal context is adequate for basic understanding but leaves many operational questions unanswered.

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?

The input schema has 100% description coverage for all parameters, so the baseline is 3. The tool description adds no extra parameter semantics beyond what the schema already 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 verb 'extract' with a specific resource 'virtual canvas data' and context 'from current page'. It also differentiates from taking a screenshot, which helps distinguish it from screenshot-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 phrase 'instead of taking screenshot' provides a clear usage context: use this tool when you need data rather than a visual capture. However, it does not explicitly mention when not to use it or name alternative sibling tools, so it falls short of a 5.

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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