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

Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint), the description discloses a rich behavioral contract: it returns a findings packet with verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation; it exposes explicit gaps[] for unanswered facets and never invents findings; standard/thorough depths also return contradictions[]. It also explains semantic excerpting and timing expectations, which is exactly the kind of contextual behavior an agent needs. No contradiction with annotations exists.

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 information-dense and well-structured: prerequisites are front-loaded, followed by the core capability, when-to-use examples, output contents, caveats, and latency. Every sentence carries operational value, and no part merely restates the tool name or title. The density is justified by the tool's complexity.

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 no output schema, the description thoroughly enumerates the return shape (findings packet with evidence, confidence, source, fetched_at, citation, gaps[], contradictions[], hop field, citation_uri). It also covers authentication requirements, plan gating, latency, alternative routing, and non-open-web scope. An agent has everything needed to select and invoke this 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?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful parameter-level context beyond the schema: depth:'thorough' requires a paid plan, and depth:'standard'/'thorough' additionally return contradictions[] and an extra hop. It also clarifies the question parameter is meant for broad or multi-part natural-language questions. This goes beyond the schema's enum descriptions without being redundant.

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 1506 STRUCTURED data sources' in one call, and explicitly contrasts itself with open-web search. It also conveys the decomposition-and-parallel-routing mechanics, making it easy for an agent to know exactly what the tool accomplishes. The focus on broad/multi-part structured-data questions clearly differentiates it from siblings like ask_pipeworx.

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?

It gives explicit when-to-use guidance: 'Best for broad/multi-part questions over structured data' and includes concrete example queries. It also states when NOT to use it: 'For a single lookup use ask_pipeworx instead' and 'If you are not signed in, use ask_pipeworx instead.' This provides both inclusion and exclusion criteria, leaving no ambiguity.

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