Crawl a website and extract emails, phone numbers, and social profiles.
Args:
website: The website URL to crawl (e.g. "example.com" or "https://example.com").
max_pages: Maximum number of pages to crawl (1-20).
| Name | Required | Description | Default |
|---|---|---|---|
| website | Yes | ||
| max_pages | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions 'crawl' which implies network requests but does not disclose potential side effects such as load on the target website, rate limits, or any safety considerations. No annotations are present to supplement this, leaving the tool's behavioral impact unclear.
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 a single concise sentence followed by a well-structured Args block. It wastes no words and presents the necessary information in a clean, readable format.
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?
The description covers the core action and parameters, but lacks details about the return format or any potential errors (e.g., what happens if the website is unreachable). Given the absence of an output schema, this missing information leaves some ambiguity for an 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?
The Args section adds meaningful detail beyond the schema: it explains the website format (including an example) and provides a numeric range for max_pages (1-20). This helps agents understand the expected input without requiring additional inference.
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 function: 'Crawl a website and extract emails, phone numbers, and social profiles.' This is a specific action on a specific resource with concrete output types, and it is easily distinguished from the sibling lookup and watch tools.
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 does not provide any guidance on when to use this tool versus the sibling tools (e.g., lookup_domain, watch_company). No conditions or scenarios are mentioned, so an agent must infer appropriate usage from the action alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.