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Lumos-Labs-HQ

Amazon Q Web Documentation Reader

read_web_documentation

Extract clean documentation content from any web URL for analysis. Choose between markdown or text output.

Instructions

Fetches and extracts clean documentation content from a web page.

This tool is designed to read documentation websites and extract the main
content in a clean, readable format suitable for analysis.

Args:
    url: The URL of the documentation page to read
    output_format: Output format - "markdown" (default) or "text"

Returns:
    Extracted documentation content with title and metadata

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
output_formatNomarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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 discloses that it fetches and extracts content, and specifies output formats and return content (title and metadata). However, it does not mention potential issues like rate limits, error handling for non-documentation pages, or behavior with non-text content. The disclosure is adequate but not exhaustive.

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 concise with two paragraphs and an Args/Returns block. Every sentence adds value: verb+resource, intended use, parameter explanations, and return description. No unnecessary text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (two parameters, one required), the existence of an output schema, and sibling tools providing context, the description is complete. It covers purpose, parameters, return values, and intended use. No gaps are apparent.

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 input schema has 0% description coverage, but the description compensates by explaining the 'url' parameter (URL of the documentation page) and the 'output_format' parameter (options: 'markdown' default or 'text'). This adds meaning beyond the schema's bare property definitions.

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 tool fetches and extracts clean documentation content from a web page. It uses a specific verb and resource (reading documentation), and the name aligns with its purpose. While it doesn't explicitly distinguish from sibling tools like extract_code_examples, the description implies it is for the main content, which is distinct enough.

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 says it is 'designed to read documentation websites', which implies appropriate usage. However, it provides no explicit guidance on when to use this tool versus alternatives (e.g., using get_page_structure for structural details). The context is implied but not directive.

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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