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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds substantial context beyond that: account/payment requirements, expected latency, the 'not invented' guarantee, the findings packet contract (verbatim evidence, confidence, source, fetched_at, pipeworx:// citation, gaps[]), and how large records are excerpted. 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?

Although the description is long, it is densely informative and front-loaded: account requirement and alternative first, then core function, then output contract, then performance expectations. Every sentence earns its place and none are filler, which is appropriate for a complex research 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?

With no output schema, the description fully covers the return packet, caveats like gaps[] and 'never invented', citation behavior, auth requirements, data scope, and runtime expectations. An agent has enough context to decide when to call it and what to expect back.

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%; both `question` and `depth` are already well described in the schema, including the detailed depth semantics and the paid thorough tier. The description reinforces broad/multi-part question phrasing and account requirements, but it does not add significant parameter meaning 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 clearly states the tool's function: grounded multi-source research over Pipeworx's structured data sources in one call, and explicitly distinguishes it from open-web search. It gives concrete example queries and names a sibling tool (ask_pipeworx) for the single-lookup case, so an agent can differentiate it from alternatives.

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: broad/multi-part questions over structured data. It also says when not to use it — for single lookups or when not signed in — and names ask_pipeworx as the alternative that works on every tier. This is direct and actionable.

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