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

Annotations already mark this as readOnly, openWorld, idempotent, and non-destructive, and the description adds substantial context on top: account requirement, parallel facet decomposition, explicit gaps[] for unanswered facets, contradictions[] for standard/thorough, semantic excerpting rather than head-truncation, citation_uri only when resolvable, and latency expectations. No statement contradicts the annotations; the description meaningfully expands behavioral understanding.

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 dense but information-rich, with very little wasted content. It front-loads the account requirement and the key alternative, then covers purpose, use cases, depth behavior, output shape, and latency. Minor structural weakness: the opening sentence mixes auth details with tool identity and paid-plan notes, pushing the core purpose slightly later than ideal.

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?

There is no output schema, so the description carries the burden of explaining return values; it does so clearly with the findings packet, verbatim evidence, confidence, source, fetched_at, citation_uri, gaps[], and contradictions[]. It also covers auth, alternatives, depth-specific behavior, citation resolvability, and latency. For a tool this complex, the description leaves little an agent needs to infer.

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 baseline is 3, but the description adds useful semantics beyond the schema: it gives concrete question examples ('compare X and Y's regulatory + financial exposure') and clarifies what each depth level does in terms of gap recovery, lead-chasing, and contradiction detection. The description does not fully replace the schema, but it enriches the meaning of both parameters.

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 across Pipeworx's 1,517 structured data sources in one call, returning a findings packet. It explicitly distinguishes itself from open-web search and from ask_pipeworx, and narrows scope to broad/multi-part questions over structured data. This is a precise verb+resource definition that separates it from 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 routing guidance: if not signed in, use ask_pipeworx instead, and for a single lookup use ask_pipeworx. It names the best-fit scenario for deep_research (broad/multi-part structured-data questions) and flags the paid-plan constraint on depth:'thorough'. This is clear when-to-use and when-not-to-use guidance.

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