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

Annotations already declare readOnly/idempotent/destructive hints, so the bar is lower, yet the description adds substantial operational context: account and paid-plan requirements, the fact that it is not open-web search, gap[] and contradictions[] behavior, never-invented assurances, always-fetchable citation_uri, semantic excerpting, and expected latency. 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 long, but appropriately so for a complex tool with many behavioral caveats. It is front-loaded with the account requirement and the key alternative, and nearly every sentence carries operational value; minor redundancy with the schema's depth descriptions is acceptable.

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 compensates by detailing the findings packet structure (evidence, confidence, source, fetched_at, citation), gaps[], contradictions[], hop field, citation_uri resolvability, and latency. It also covers auth limitations, use-case routing, and failure modes for unsupported topics — complete for safe invocation.

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 both parameters already have detailed descriptions, so the baseline is 3. The description adds extra meaning by tying depth='thorough' to a paid plan and by framing the depth options in terms of second-hop recovery and contradiction scans — beyond the schema's wording.

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 1,500 structured data sources, decomposing questions into facets and routing to 5,743 tools in parallel. It explicitly differentiates from open-web search and from ask_pipeworx, making the tool's scope unmistakable.

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, with named alternatives and conditions (single lookup → ask_pipeworx; breaking/current news → ask_pipeworx; not signed in → ask_pipeworx). It also explains when to choose quick vs standard vs thorough depth, leaving little to inference.

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