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

Annotations declare readOnly=true, openWorld=true, idempotent=true, and destructive=false, so the description is not required to restate those. It adds substantial behavioral detail beyond annotations: returns a findings packet with verbatim evidence, confidence, source, fetched_at, and pipeworx:// citations; explicitly never invents answers and reports gaps[]; explains hop iteration, contradictions[], semantic excerpting, and expected latency. This rich behavior disclosure goes well beyond what annotations provide.

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 information-dense and front-loaded with the critical signup/account constraint, but it is very long and packs many distinct behavioral promises into a single paragraph. While every sentence earns its place, the lack of paragraph breaks or bullet structure makes it harder to parse; it is closer to a spec sheet than a scannable tool description.

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?

For a complex tool with two parameters, an output-finding behavior not documented by any output schema, and important account/depth constraints, the description covers all the essential context: prerequisites, alternatives, expected latency, return shape, failure behavior (gaps[], contradictions[]), citation fetchability, and scope boundaries. Nothing critical 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 description coverage is 100%, so the schema already documents both parameters well. The description adds meaning beyond the schema by clarifying what each depth level actually does (quick=single hop, standard=gap recovery + contradictions[], thorough=6 facets + iterative lead-chasing) and confirms that broad/multi-part natural-language questions are acceptable. This is helpful incremental value, though the schema alone is already strong.

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 is specific about what this tool does: grounded multi-source research across Pipeworx's 1500 structured data sources in one call, with decomposition into facets and parallel routing to 5,743 tools. It explicitly contrasts itself with open-web search and names sibling ask_pipeworx for single lookups, making its purpose and differentiation clear.

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 provides explicit when-to-use guidance: best for broad/multi-part questions over structured data, with concrete examples. It also states when NOT to use it: for single lookups use ask_pipeworx, and for breaking/colloquial current-news topics prefer ask_pipeworx because deep_research returns mostly empty gaps[]. Account requirements and depth-tier conditions are also spelled out.

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