discover

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

Without annotations, the description carries the burden, and it does well by explaining the tool's cheap-first nature, optional navigation, light JS execution, and merging of sources. It implies a read-only discovery operation, but does not explicitly state side effects of navigation on current page state.

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 concise at two sentences, front-loaded with the core purpose, and every sentence adds value. No wasted words.

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 complexity (7 parameters, no output schema), the description provides a good overview of what the tool does and when to use it. However, it lacks details on the return format (the ranked graph) and how 'provenance' and 'escalation hints' are presented, which a fully complete description would include.

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 input schema has 100% coverage with descriptions for all 7 parameters. The tool's description adds no new semantic meaning beyond what is already in the schema, so the baseline score of 3 applies.

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 as high-level cheap-first information discovery, detailing specific actions like navigating, running JS, and merging routes. It distinguishes itself from siblings by framing itself as the first step before 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 description gives a clear usage hint: 'Use this when the task is to find where information lives before extracting it.' This provides context, though it does not explicitly exclude scenarios where more specific tools like route_discover or network_extract would be better.

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