lead_extract

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 mentions using a headless browser and optional LLM parsing, which adds behavioral context. However, it does not disclose whether the tool is read-only, rate limits, or error handling, so transparency is moderate.

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, well-structured sentence with no fluff. It is front-loaded with key information and every word adds value.

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 simplicity, the description covers the main purpose and inputs. However, it lacks information about output format, error conditions, and prerequisites (e.g., URL must be accessible). No output schema exists, so some return details would be helpful.

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?

Schema description coverage is 0%, so the description must compensate. It implicitly covers 'url' by stating 'from a single URL' and hints at 'deep' by mentioning 'optional LLM parsing'. However, it does not explicitly link parameters or explain the boolean semantics of 'deep' (e.g., what happens when true vs false).

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 verb 'deep-extract' and the resource 'company info from a single URL', listing specific fields (name, emails, industry, size). It distinguishes itself from sibling tools like lead_discover and lead_generate by focusing on a single URL extraction.

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 context is clear: use this tool when you have a specific URL to extract company info. However, there is no explicit guidance on when not to use it or alternatives, though the description implies it is the correct tool for URL-based extraction.

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