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read_website

read_website

Extract web content and convert it to clean Markdown format for reading documentation, analyzing information, and gathering data from websites while preserving links and structure.

Instructions

Fast, token-efficient web content extraction - ideal for reading documentation, analyzing content, and gathering information from websites. Converts to clean Markdown while preserving links and structure.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
pagesNo
cookiesFileNo
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 key behavioral traits: 'fast, token-efficient' (performance characteristics), 'converts to clean Markdown' (output format), and 'preserving links and structure' (content handling). However, it lacks details on error handling, rate limits, authentication needs, or what happens with invalid URLs, which are important for a web scraping tool.

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 highly concise and well-structured in two sentences. The first sentence establishes the core functionality and ideal use cases, while the second explains the output format and key features. Every word earns its place with no redundancy or unnecessary elaboration.

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?

Given the tool's moderate complexity (web scraping with 3 parameters) and lack of annotations or output schema, the description is partially complete. It covers the purpose, performance, and output format well, but it misses crucial details like parameter semantics, error conditions, and return value structure, which are needed for effective tool 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?

The schema description coverage is 0%, and the description provides no information about the three parameters (url, pages, cookiesFile). It doesn't explain what 'pages' or 'cookiesFile' mean, their formats, or how they affect the extraction process. This leaves significant gaps in understanding parameter usage beyond what the bare schema 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 tool's purpose with specific verbs ('extraction', 'reading', 'analyzing', 'gathering') and resources ('web content', 'websites', 'documentation'). It distinguishes itself by emphasizing 'fast, token-efficient' conversion to 'clean Markdown while preserving links and structure', which provides a unique value proposition even without sibling tools.

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 provides implied usage guidance by listing ideal scenarios ('reading documentation, analyzing content, and gathering information from websites'), but it does not explicitly state when to use this tool versus alternatives or mention any exclusions. With no sibling tools, the lack of comparative guidance is less critical, but it still doesn't offer explicit when/when-not instructions.

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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