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

Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint), the description discloses account requirements, paid tier conditions, non-open-web grounding, parallel tool routing, the exact findings-packet shape (verbatim evidence, confidence, source, fetched_at, citation, gaps[], contradictions[]), the citation_uri fetchability guarantee, semantic excerpting of large records, and expected latency (15-60s, up to ~90s for thorough). 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 long but appropriately so for a tool of this complexity. It is front-loaded with the most critical constraint (account required) and the core differentiator (NOT open-web search), then proceeds through output structure, depth semantics, citation behavior, and latency. Every sentence conveys operational information; the only minor redundancy is mentioning ask_pipeworx twice, but each instance serves a different routing context.

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 fully covers return values: findings packet fields, gaps[] for unanswered facets, contradictions[] for standard/thorough, hop field, citation_uri only when fetchable, and semantic excerpting. It also covers edge cases like unfetchable citations and slow responses. An agent has all the information needed to invoke the tool and interpret results.

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%, but the description adds significant meaning beyond the enum values. It explains that depth:'standard' re-angles unanswered gaps and adds contradictions[], depth:'thorough' chases leads from the first pass and costs money, and that the 'question' parameter can be broad/multi-part natural language. This contextualizes the parameters for decision-making far better than the schema alone.

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 names a specific verb-resource pair: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources... in ONE call.' It details the mechanism (decompose into facets, route to 5,798 tools in parallel, return findings packet) and explicitly distinguishes itself from open-web search and ask_pipeworx. Concrete examples like 'compare X and Y's regulatory + financial exposure' make the intended use unmistakable.

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 states both when to use and when to use alternatives: 'Best for broad/multi-part questions over structured data', 'For a single lookup use ask_pipeworx instead', and 'If you are not signed in, use ask_pipeworx instead'. It also guides depth selection by noting that 'thorough' requires a paid plan and that standard/thorough add gap recovery and contradictions scanning.

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