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

Annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint=false) are already strong; the description adds substantial context on top: account/paid-tier requirements, 15-90s latency expectations, the findings-packet return shape (verbatim evidence + confidence + source + fetched_at + gaps[] + contradictions[]), a no-hallucination guarantee ('never invented'), and semantic-excerpting behavior. No contradiction with annotations — readOnly agrees with a research tool.

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 contains a leaked editorial placeholder — '(one large block about second iteration / hop / `hop` field / citation_uri...' — that reads as author notes left in the final text. Content is also duplicated: the citation_uri/resolvable-URI guarantee and the contradictions[] scan each appear twice nearly verbatim, and depth-tier behavior is repeated across the schema, the garbled block, and the clean text. Front-loading is good (account requirement first), but the repetition and unedited block are material structural defects.

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 and only 2 parameters, the description delivers the full operational picture: auth requirements, pricing tiers, latency, return packet structure, citation resolvability, and gap/contradiction behavior. Nothing an agent needs to call it correctly is missing — though the garbled duplication makes that information harder to extract cleanly than it should be.

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% and the depth enum description already documents facet counts, hops, and the contradictions scan. The description adds value beyond the schema by tying 'thorough' to a paid plan requirement and giving latency expectations per tier. This exceeds the baseline-3 for full schema coverage but does not drastically re-explain the 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?

States a precise verb+resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources... in ONE call' with explicit negation ('this is NOT open-web search'). Clearly distinguishes from siblings by naming ask_pipeworx for single lookups and describing the facet-decomposition mechanism.

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?

Gives explicit routing rules: 'If you are not signed in, use ask_pipeworx instead' and 'For a single lookup use ask_pipeworx instead.' Also frames the ideal use case positively: 'Best for broad/multi-part questions over structured data' with concrete examples. No ambiguity about when this tool beats its alternatives.

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