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

Annotations already declare readOnly/openWorld/idempotent, and the description adds substantial behavior beyond those: account requirement, parallel routing to 5,798 tools, gaps[] semantics with 'never invented', contradictions[] on standard/thorough, semantic excerpting, fetchable citation_uri guarantees, and expected latency. No contradiction with annotations exists.

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 dense, and nearly every sentence carries operational or selection-relevant information. It is front-loaded with the account requirement and the primary alternative, then proceeds through behavior, return packet, depth semantics, and latency. It could be slightly tightened, but for a complex tool with no output schema the detail is largely earned.

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 tool's complexity, the 100% schema coverage for parameters, and the absence of an output schema, the description is remarkably complete. It explains what the findings packet contains, how gaps and contradictions behave, how citations are guaranteed fetchable, which depth to choose, what latency to expect, and when to use ask_pipeworx instead. An agent has enough context to invoke it 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?

Schema coverage is 100%, so the baseline is 3, but the description adds real value beyond the schema: it explains depth tiers in behavioral terms (quick=3 facets, standard=3 with gap recovery and contradictions, thorough=6 paid with iterative hops) and clarifies that broad/multi-part natural-language questions are acceptable. This is more than the schema alone provides.

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 specific verb and resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources... in ONE call.' It explicitly distinguishes itself from open-web search and names the sibling alternative (ask_pipeworx) for different use cases, so an agent can tell them apart.

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 questions over structured data' and 'For a single lookup use ask_pipeworx instead.' It also covers the signed-out fallback ('If you are not signed in, use ask_pipeworx instead'), and explains depth-tier selection including the paid requirement for 'thorough.'

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