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

Annotations already signal read-only, open-world, and idempotent behavior, but the description goes well beyond that by explaining the output packet contents (verbatim evidence, confidence, source, fetched_at, stable pipeworx:// citations), the explicit gaps[] for unanswered facets, and the 'never invented' guarantee. It also discloses depth-dependent behaviors like gap recovery, contradictions[], hop/citation_uri fields, semantic excerpting, and expected latency ranges—none of which are inferable from annotations alone.

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 front-loaded with account requirements, the fallback tool, and the core behavior, and its longer passages are information-dense and useful. However, the instruction 'For a single lookup use ask_pipeworx instead' is repeated multiple times nearly verbatim, creating redundancy that weakens conciseness.

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 present, the description carries the full burden of explaining return values, and it does so thoroughly: findings packet fields, gaps[], contradictions[], citation_uri semantics, excerpting behavior, latency, and authentication/paid-tier prerequisites. An agent has enough context to decide when and how to invoke this tool 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?

The input schema already covers both parameters with 100% description coverage, so the baseline is high. The description adds value by noting that depth 'thorough' requires a paid plan and by framing the question parameter as naturally broad/multi-part, but most parameter-level meaning is already present in the 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 specifies a concrete verb and resource ('Grounded multi-source research across Pipeworx's 1506 STRUCTURED data sources') and explicitly contrasts itself with open-web search and the ask_pipeworx sibling. It also includes example queries and a direct 'For a single lookup use ask_pipeworx instead' instruction, making the tool's distinct role immediately clear.

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 provides explicit when-to-use guidance: best for broad/multi-part questions over structured data, while single lookups should use ask_pipeworx. It also gives an account-based fallback rule ('If you are not signed in, use ask_pipeworx instead') and example queries, so an agent can select this tool versus siblings without ambiguity.

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