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

With annotations already establishing readOnly, idempotent, and non-destructive behavior, the description adds substantial operational context: it returns verbatim evidence with confidence and source fields, never fabricates missing findings but reports gaps[], surfaces contradictions at certain depths, semantically excerpts large records, and states 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 dense and front-loaded with the most critical constraint (account requirement and fallback tool). It is longer than ideal and somewhat parenthetical-heavy, with some depth details duplicated from the schema, but nearly every sentence carries operational value for a complex 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?

Because there is no output schema, the description carries the full burden of explaining return semantics, and it does: findings packet with evidence, confidence, source, fetched_at, citation URI, gaps[], contradictions[], hop field, citation fetchability, and latency. Combined with authentication, tier, and usage guidance, an agent has enough context to invoke the tool 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 description coverage is 100%, and both parameters are already well documented: question is natural language and broad/multi-part is fine, while depth already details facet counts, hops, and paid status. The description largely restates these semantics, adding only latency expectations and auth context, so it does not significantly extend 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 states a clear, specific function: grounded multi-source research across Pipeworx's structured data sources in a single call, with decomposition and parallel routing. It explicitly distinguishes itself from open-web search and from ask_pipeworx, making sibling differentiation immediate and unambiguous.

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 questions over structured data'), explicit when-not-to-use guidance ('For a single lookup use ask_pipeworx instead'), and an auth-based routing rule ('If you are not signed in, use ask_pipeworx instead'). It also conditions depth choices on paid access, 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.