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

Despite helpful annotations, the description goes well beyond them: it discloses account/auth requirements, plan gating, parallel routing across tools, latency expectations, gap reporting, contradiction scanning, citation behavior, and the guarantee that findings are never invented. No contradiction with annotations was found.

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 long but dense, and it front-loads the account gate and primary alternative before diving into behavior. Some depth details duplicate the schema, so it is not perfectly lean, but the length is largely justified by the tool's complexity and the absence of an output schema.

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?

With no output schema, the description carries the full burden of explaining what the agent will receive, and it does: findings packet, evidence, confidence, source, fetched_at, stable citation, gaps, contradictions, excerpting, and latency. For a two-parameter tool, nothing material is missing.

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 100%, so the baseline is 3. The description adds a bit beyond the schema by tying thorough depth to a paid plan and giving runtime expectations, but much of the depth-enum behavior is already documented in the input schema.

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 identifies the tool as grounded multi-source research over Pipeworx's structured data sources, and explicitly contrasts it with open-web search and with ask_pipeworx. It names a specific verb, resource, and output, so an agent can distinguish it from siblings without opening the schema.

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?

Usage guidance is explicit: use this for broad/multi-part questions over structured data, use ask_pipeworx for single lookups or when not signed in. It also notes the paid-plan requirement for thorough depth, so the agent knows the preconditions and the main alternative.

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