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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which covers the safety profile. The description goes far beyond that with genuinely useful behavioral context: latency expectations (15-60s, up to ~90s), gap recovery behavior ('never invented', explicit gaps[]), contradiction scanning, the parallel decomposition strategy, citation resolvability ('present only when the source emits one'), and semantic excerpting. Nothing about the tool's observable behavior is hidden.

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?

Every sentence earns its place — the account gate is front-loaded before anything else, and the dense middle section packs an unusual amount of behavioral detail without fluff. It is long, but the tool is legitimately complex (two params, no output schema, rich runtime behavior), so the length is justified. Minor redundancy exists: the depth-level mechanics repeat what the schema already documents.

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 exhaustively: findings packet with verbatim evidence, confidence, source, fetched_at, citation URI, gaps[], contradictions[], and the hop field. It also covers prerequisites (account, paid plan), latency, data-source scope (1517 sources, 5,798 tools), and behavior on unanswerable facets. Nothing an agent needs to invoke this tool correctly is missing.

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 per the baseline rule a 3 is warranted even with no description-side info. However, the description adds real value beyond the schema: it specifies that 'thorough' requires a paid plan, gives latency expectations per depth, and provides example questions ('compare X and Y's regulatory + financial exposure') that help an agent formulate a good `question` value. This is supplementary semantic guidance the schema doesn't offer.

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' — and explicitly disambiguates from siblings with 'this is NOT open-web search.' It also carves out its niche versus ask_pipeworx ('For a single lookup use ask_pipeworx instead'), so an agent can distinguish it from every one of the 33 siblings without opening another tool.

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 ('Best for broad/multi-part questions over structured data'), when-not-to-use ('For a single lookup use ask_pipeworx instead'), an alternative gate ('If you are not signed in, use ask_pipeworx instead — it works on every tier'), and a hard prerequisite (account, paid plan for thorough). No usage condition 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.