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

Even though annotations already carry readOnlyHint=true and idempotentHint=true, the description adds substantial behavior beyond them: authentication and paid-tier requirements, latency envelope (15-60s, ~90s for thorough), the "never invented" guarantee via explicit gaps[], contradictions[] for standard/thorough, semantic passage excerpting instead of head-truncation, and the citation_uri resolvability condition. This meaningfully exceeds what the annotations alone disclose, and it does not contradict them.

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 appropriately front-loaded with the most operationally critical gate (account required, use ask_pipeworx if unsigned) and every sentence carries information. However, it is structured as one very dense paragraph with nested em-dash asides and parentheticals (plan caveat, citation_uri condition, excerpting note) that an agent must parse linearly; a bulleted or sentence-per-concept structure would materially improve scannability.

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 correctly takes on the burden of explaining return semantics: the findings packet fields (verbatim evidence, confidence, source, fetched_at, stable citation), gaps[], contradictions[], the hop field, and excerpting behavior are all covered. Combined with full schema parameter coverage and rich annotations, nothing an agent needs to select and invoke the tool correctly is missing.

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%, and the schema's depth description already explains hop counts, gap recovery, contradictions[], and the paid requirement for thorough — so the baseline of 3 applies. The description adds only marginal parameter value: example questions that illustrate good input and the latency trade-off by depth. The schema carries 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 states a precise scope: "Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources ... in ONE call," with the explicit negative "this is NOT open-web search." It names concrete example questions ("compare X and Y's regulatory + financial exposure") and distinguishes itself from adjacent siblings like ask_pipeworx, so an agent can tell it apart without inspecting other schemas.

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/when-not guidance: "If you are not signed in, use ask_pipeworx instead," "For a single lookup use ask_pipeworx," and "For current news ... prefer ask_pipeworx." The positive case is equally explicit — "Best for broad/multi-part questions over structured data" — so the agent receives both selection criteria and named alternatives with no inference required.

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