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

Annotations carry readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, and the description builds meaningfully on this by adding auth requirements, paid-tier caveats, output guarantees (gaps[] never invented), citation resolvability caveats, contradictions[] behavior, semantic excerpting, and latency expectations. It also clarifies this is not open-web search. No contradiction with annotations.

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, information-rich, and front-loads the account requirement before anything else. It is longer than strictly necessary and partly duplicates the schema's depth enum descriptions, but each passage earns its place for such a complex tool. A trimmed version would score higher.

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?

Given the complexity and the lack of an output schema, the description covers all essential operational aspects: authentication, plan restrictions, alternative routing, input style, output content (findings packet with verbatim evidence, confidence, source, fetched_at, citation_uri), gap handling, contradiction detection, and latency. An agent has everything needed to invoke it correctly and set expectations.

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%, with detailed enum descriptions, so the baseline is 3. The description adds some extra value: concrete example questions, latency expectations per depth, and the paid-plan constraint for 'thorough'. However, core parameter semantics are already fully documented in the schema, so the description's additional contribution is moderate.

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 an exact capability: 'Grounded multi-source research ... across Pipeworx's 1517 STRUCTURED data sources ... in ONE call', with decomposition and parallel routing to specialized tools. It explicitly distinguishes itself from open-web search and from the sibling ask_pipeworx, so an agent can tell exactly what this tool is for.

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 guidance: 'If you are not signed in, use ask_pipeworx instead' and 'For a single lookup use ask_pipeworx instead', plus 'Best for broad/multi-part questions over structured data'. This is precisely the kind of when-to-use versus alternative direction that prevents agent mis-selection.

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