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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds substantial context on top: account/pricing requirements (thorough needs paid plan), latency expectations (15-60s, up to ~90s), the honesty guarantee (explicit gaps[], 'never invented'), citation fetchability, and which depth levels return contradictions[]. No contradiction with annotations — readOnly is consistent with 'returns a findings packet'.

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?

Long (~350 words) but dense: auth gate and alternative tool are front-loaded first, and nearly every clause carries unique information (sources, parallel routing, packet contents, gaps, latency, pricing). Minor redundancy with the schema's depth parameter prevents a 5, but the length is justified for a tool this complex with no output schema.

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 enumerates the findings packet (verbatim evidence, confidence, source, fetched_at, citation_uri, gaps[], contradictions[]) and covers auth, cost, latency, scope exclusions, and sibling routing. An agent has everything needed to decide, invoke, and interpret the 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?

Schema coverage is 100% and the schema's depth description already explains facet counts, hop behavior, and contradiction scans. The description adds genuine value beyond the schema: the paid-plan requirement for 'thorough', latency per depth tier, and the hop/citation semantics. It partly duplicates the schema but earns above-baseline credit for the pricing gate.

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?

States a specific verb ('research'), resource ('Pipeworx's 1517 STRUCTURED data sources'), and mechanism ('routes each facet to one of 5,798 tools IN PARALLEL'). Explicitly distinguishes from open-web search and from ask_pipeworx, so an agent can pick it out of the 29 sibling tools without guessing.

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 when-to-use ('Best for broad/multi-part questions over structured data') and when-not-to-use ('For a single lookup use ask_pipeworx instead'), names the alternative by tool name, and even gates on auth state ('If you are not signed in, use ask_pipeworx instead'). Nothing is left to inference.

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