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

Annotations already mark this readOnly, non-destructive, idempotent, and open-world. The description adds substantial behavioral context beyond those annotations: account requirement, expected latency (15-60s, ~90s for thorough), parallel decomposition into facets, output shape (findings with evidence, confidence, source, fetched_at, pipeworx:// citation), explicit gaps[] when data is unavailable, and 'never invented' guarantees. It also explains the citation_uri is only present when fetchable and that large records are semantically excerpted, giving agents accurate expectations about edge behavior.

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 nearly every sentence carries distinct operational information. The account requirement and alternative tool routing are front-loaded, followed by the core mechanism, then output and latency details. Structure could be improved with clearer paragraph separation, but it is dense and deliberately organized rather than padded.

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?

Given the tool has no output schema and only 2 parameters, the description fully compensates: it enumerates the return fields, gap handling, contradiction scan behavior, citation fetchability guarantee, account/premium constraints, and time expectations. An agent has enough information to correctly select the tool, choose a depth, and interpret the result without missing critical operational details.

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 baseline is 3. The description adds value beyond the schema by explaining that question can be 'broad/multi-part' and that decomposition is the point, and by clarifying the real-world implications of depth tiers (paid plan for 'thorough', hop behavior, contradictions scan). This elevates it above baseline because an agent gains practical selection and invocation knowledge not present in 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 specific verb-resource pair: 'grounded multi-source research across Pipeworx's 1500 STRUCTURED data sources' in one call, and explicitly distinguishes itself from open-web search ('this is NOT open-web search'). It also differentiates from sibling ask_pipeworx by positioning deep_research for broad/multi-part questions over structured data. This is clear, specific, and non-tautological.

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 explicitly names the alternative: 'For a single lookup use ask_pipeworx instead'. It also states when not to use it due to account tier ('If you are not signed in, use ask_pipeworx instead') and notes the paid requirement for 'thorough' depth.

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