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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description goes well beyond that by disclosing the findings packet structure, gaps[] non-invention guarantee, contradictions[] for standard/thorough, hop fields, citation_uri resolvability, semantic excerpting, latency expectations, and paid-tier requirements. It adds rich behavioral context without contradicting the 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 long and single-paragraph, and it starts with account requirements rather than the core function, so it is not perfectly front-loaded. However, almost every sentence carries selection- or invocation-relevant detail—alternatives, depth semantics, result shape, caveats, and latency—so the length is justified by the tool's complexity.

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, the description carries the full burden of explaining return values, and it does so thoroughly: findings packet, verbatim evidence, confidence, source, fetched_at, pipeworx:// citation, gaps[], contradictions[], hop, and citation_uri. It also covers auth requirements, latency, when NOT to use it, and depth behaviors—leaving little an agent needs to decide and call correctly.

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?

The input schema already covers both parameters at 100%, including enum descriptions for depth. The description adds further meaning: thorough is paid, standard performs gap recovery and contradiction scans, thorough chases leads, and latency varies by tier. This is meaningful added context beyond the schema.

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 1,497 structured data sources, with decomposition into facets and parallel routing. It clearly distinguishes itself from ask_pipeworx and explicitly states it is NOT open-web search, so an agent can tell it apart 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, while single lookups should use ask_pipeworx, breaking/colloquial current-news topics should prefer ask_pipeworx, and unsigned-in users should use ask_pipeworx. It also explains depth tier selection, making the routing decision explicit.

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