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

The description is rich beyond the annotations: it explains account/paid-tier requirements, that it decomposes questions and routes to thousands of tools in parallel, that findings include verbatim evidence, confidence, source, fetched_at, pipeworx:// citations, gaps[], contradictions[], and that large records are semantically excerpted. It also discloses expected latency (15-60s, up to ~90s for thorough), which is useful behavioral context not present in annotations.

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 densely informative, and it front-loads the most important gate (account required) and alternative (ask_pipeworx) before explaining behavior and return details. Some parenthetical asides are heavy, and a few details are repeated from the schema, but the length is largely justified by the tool's complexity.

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 has no output schema, the description compensates well by specifying the findings packet components, citation behavior, gaps[], contradictions[], semantic excerpting, and timing. It also covers authentication requirements and the fallback tool, making the definition complete enough for an agent to select and invoke it correctly.

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 100%, so the schema already documents both 'question' and 'depth' fully, including enum meaning. The description adds the paid-plan constraint for 'thorough' and latency expectations, but most parameter-level meaning is already in the schema. This is the baseline 3 case where the schema does the heavy lifting.

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 names a specific verb and resource: "Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources" in one call. It clearly distinguishes itself from open-web search and from the sibling ask_pipeworx, so an agent can tell what it does.

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 explicit usage guidance: sign-in is required, "If you are not signed in, use ask_pipeworx instead," and "For a single lookup use ask_pipeworx." It also says it is "Best for broad/multi-part questions over structured data," naming the alternative and the selection condition.

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