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

Annotations already mark the tool read-only and idempotent, and the description adds substantial behavioral detail beyond that: parallel facet decomposition, explicit gaps[] that are 'never invented', contradiction[] scanning for standard/thorough, semantic excerpting of large records, resolvable citation_uri values, and latency expectations. None of this conflicts with the 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 well-structured and front-loaded: account prerequisite and fallback first, then core purpose, then usage guidance, then depth details, then output/latency. Every section adds distinct value for a complex tool, though it is wordier than strictly necessary.

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 burden of explaining return values, and it does so thoroughly: findings packet fields (verbatim evidence, confidence, source, fetched_at, pipeworx:// citation), gaps[], contradictions[], hop field, and citation_uri. It also covers prerequisites, depth variations, alternatives, and latency. Given the tool's complexity, this is remarkably complete.

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 both parameters are already described in the schema. The description adds extra meaning beyond the schema, especially for depth: it ties each level to concrete behavior ('standard' re-angles gaps, 'thorough' chases leads and is paid) and notes latency implications ('thorough ... up to ~90s'). For question, it reinforces that broad/multi-part questions are the intended use. This goes beyond simple repetition.

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 and resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources' and explains the core process: 'Decomposes your question into focused facets, routes each to the right one of 5,798 tools IN PARALLEL, and returns a findings packet'. It explicitly distinguishes itself from open-web search and from the sibling ask_pipeworx, so an agent can reliably tell them apart.

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 and when-not-to-use guidance: 'Best for broad/multi-part questions over structured data', 'For a single lookup use ask_pipeworx instead', and 'For BREAKING or colloquial CURRENT-NEWS ... prefer ask_pipeworx'. It also states the prerequisite and fallback: 'If you are not signed in, use ask_pipeworx instead'. This fully covers selection among alternatives.

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