scrape_as_markdown

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds valuable context about capabilities ('unlock any webpage even if it uses bot detection or CAPTCHA') and output format ('MarkDown language'), but doesn't cover important behavioral aspects like error handling, rate limits, authentication requirements, or what 'advanced options' specifically entail.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is perfectly concise with two sentences that each earn their place. The first sentence states the core functionality and output format, while the second adds important capability context. There's zero wasted language and it's front-loaded with the main purpose.

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

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

Given the tool's complexity (web scraping with advanced capabilities), no annotations, no output schema, and only 0% schema description coverage, the description is adequate but has clear gaps. It covers the basic purpose and some capabilities well, but doesn't address error cases, performance characteristics, or detailed behavioral expectations that would be important for an AI agent.

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

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

With 0% schema description coverage and only 1 parameter, the description compensates well by explaining the parameter's purpose ('scrape a single webpage URL') and context. While it doesn't provide format details beyond what the schema indicates (URI format), it adds meaningful semantic context about what the URL parameter represents in this scraping context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 ('scrape a single webpage URL') and resources ('webpage'), and distinguishes it from siblings by specifying 'single webpage' (vs. batch operations) and 'MarkDown language' output format. It provides a complete picture of what the tool does.

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

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 ('scrape a single webpage URL'), but doesn't explicitly mention when not to use it or name alternatives. It implies usage for single-page scraping with advanced extraction needs, but lacks explicit comparison to sibling tools like scrape_batch for multiple URLs.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.