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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds substantial context beyond annotations: account/plan requirements, expected latency ('15-60s', thorough 'up to ~90s'), the internal decompose-and-route mechanism, output shape (gaps[], contradictions[], hop field, citation_uri), and the guarantee that citations are always fetchable. 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 information-dense and front-loaded with the most critical constraint (account required). However, it is a single wall-of-text paragraph with some redundancy — contradictions[] and the multi-step resolution behavior are each mentioned twice — which slightly hurts scannability.

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: findings packet fields, gaps[] for unanswered facets, contradictions[], the hop field, and citation_uri behavior. It also covers auth tiers, latency, and source scope. Nothing an agent needs to invoke or interpret 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% and the depth enum description is already detailed, so baseline is 3. The description adds meaning beyond the schema: it ties 'thorough' to the paid plan, gives latency expectations per depth, and provides concrete example questions for the 'question' parameter. This lifts it above baseline.

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+resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources ... in ONE call', and explicitly carves out what it is not ('this is NOT open-web search'). It differentiates itself from siblings by naming when to use ask_pipeworx instead, so an agent can select it correctly without opening the schema.

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?

Provides explicit when-to-use guidance: 'Best for broad/multi-part questions over structured data' with concrete examples, and explicit when-not-to-use: 'For a single lookup use ask_pipeworx instead' and 'If you are not signed in, use ask_pipeworx instead'. The alternative tool is named and the selection condition is unambiguous.

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