Extract Leads

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 reveals that an LLM is used, which is useful, but it does not disclose whether the operation is read-only, what 'supported lead fields' means, potential failure modes, or any rate or auth constraints. This leaves significant behavioral ambiguity.

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?

A single sentence, 13 words, with no wasted filler. The key elements (action, resource, input, method) are present and front-loaded. It is appropriately concise for a simple tool.

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 tool has only 2 parameters and an output schema exists, which reduces the need to explain return values. However, the description lacks guidance on usage and parameter semantics, and the absence of annotations leaves transparency gaps. It is minimally viable but not fully complete for an agent to use with confidence.

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 coverage is 0% with no descriptions. The description adds little meaning beyond the parameter names: it references 'public page content' which maps to 'content', and 'sourceUrl' is implied but not explicitly described. For a 0% coverage case, the description should compensate, but it does not.

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 extracts supported lead fields from supplied public page content using a configured LLM. This distinguishes it from siblings like scrape_page (which fetches content) and find_leads (which likely searches or discovers leads). The verb 'extract' and resource 'lead fields' are specific.

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?

No explicit guidance on when to use this tool versus alternatives. The description implies it is used after obtaining page content, but does not mention when not to use it or reference sibling tools. With no exclusions or context, the agent is left to infer the appropriate scenario.

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