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

With read-only annotations already present, the description adds substantial behavioral context: account/paid-plan requirements, one-call parallel decomposition, gaps[] and contradictions[] arrays, citation_uri semantics, semantic excerpting, and expected latency. It also notes the tool never invents evidence, a meaningful behavioral promise.

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 long but densely informative, front-loading the account requirement and the critical ask_pipeworx alternative. There is minor redundancy around single-lookup routing, but most sentences add distinct operational value for a complex tool.

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?

Despite no output schema, the description covers what the findings packet contains, how facet gaps are handled, what citation_uri means, how contradictions appear, and how long the call may take. Given the tool's complexity, nothing essential for correct invocation or expectation-setting 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 coverage is 100% and the schema already explains both parameters, so the baseline is 3. The description adds value by clarifying the paid gate on depth:'thorough', the iterative gap-recovery behavior for standard/thorough, and time expectations. This is useful but somewhat redundant with the schema's depth enum descriptions.

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 names a specific verb and resource: 'Grounded multi-source research across Pipeworx's 1506 STRUCTURED data sources' and explicitly distinguishes itself from open-web search and ask_pipeworx. It makes the tool's scope unmistakable and readily differentiates 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 when-to-use guidance: best for broad/multi-part structured-data questions, and explicitly tells agents to use ask_pipeworx for single lookups, breaking/colloquial news, and when not signed in. This gives clear routing criteria among siblings.

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