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

Annotations already signal read-only, idempotent, and non-destructive behavior. The description adds substantial behavioral detail beyond that: account and paid-plan requirements, decomposition into parallel facets across 5,798 tools, the exact findings-packet shape, explicit gaps[] for unanswered facets, and the guarantee that findings are never invented. This goes well beyond the structured 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 information-rich, front-loading the account requirement and the key alternative tool. However, it repeats the ask_pipeworx routing message ('If you are not signed in...' and 'For a single lookup use ask_pipeworx instead...'), and the final 'Second iteration...' sentence is structurally awkward. Minor redundancy keeps it from a perfect score.

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?

Even though there is no output schema, the description explains the return shape thoroughly: findings packet, verbatim evidence, confidence, source, fetched_at, pipeworx:// citations, gaps[], and contradictions[] coverage for standard/thorough. It also covers prerequisites, alternatives, and input expectations, so 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?

The input schema already provides 100% parameter coverage, including detailed depth semantics and the paid requirement for 'thorough'. The description adds value by reinforcing the account requirement and giving concrete example question shapes for the 'question' parameter, but most parameter-level meaning still comes from the schema itself.

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 a specific action and resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources' in ONE call, and explicitly distinguishes itself from open-web search. It also names what it returns—a findings packet with evidence, confidence, source, and citations—so an agent knows exactly what this tool is for.

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') and explicit when-not-to-use guidance ('For a single lookup use ask_pipeworx instead'). It also states the account/plan precondition and tells unsigned-in users to use ask_pipeworx instead, which is precisely the kind of routing information an agent needs.

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