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

Beyond the readOnly/idempotent annotations, the description discloses account and paid-tier requirements, expected latency, the never-invented gaps[] behavior, contradictions[] in standard/thorough, semantically excerpted records, and citation_uri resolvability. It even explains when the tool will return mostly empty gaps[], which is critical for setting agent expectations.

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 and dense, but it front-loads the critical account condition and core purpose, then layers behavioral details and alternatives. Every clause adds information, though some depth-option details repeat the schema and the use of heavy capitalization/emphasis slightly reduces polish.

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?

For a complex tool with no output schema, the description fully covers return structure, failure/gap semantics, latency, pricing, prerequisites, limitations, and sibling routing. An agent has enough information to call it correctly and interpret its result without guessing.

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 already describes both parameters in detail, including depth variants, facet counts, gap recovery, and the paid nature of thorough, and says broad/multi-part questions are fine. The description largely restates this in prose and adds only latency and account context, which is behavioral rather than parameter-specific. Baseline 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 names a specific verb/resource: grounded multi-source research across Pipeworx's 1497 structured data sources, with decomposition into facets and parallel routing. It explicitly distinguishes itself from open-web search and from ask_pipeworx, so an agent can select it accurately among siblings.

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 when-to-use and when-not-to-use guidance: use for broad/multi-part structured-data questions; use ask_pipeworx for single lookups and for breaking/colloquial current-news topics; if not signed in, use ask_pipeworx. It also names alternatives and the exact conditions that select them.

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