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

The annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior, but the description goes well beyond them. It discloses the parallel routing through 5,724 tools, the findings packet shape (verbatim evidence + confidence + source + fetched_at + citation), the gaps[] never-invented guarantee, contradictions[], hop fields, citation_uri resolvability, semantic excerpting, latency expectations, and the paid tier requirement for thorough depth. 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 it is front-loaded with the account constraint, usage guidance, and the central differentiator ('this is NOT open-web search') before diving into behavioral specifics. Every sentence carries distinct information about sources, output shape, depth semantics, or latency. Minor trims could tighten it, but the length is largely 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?

There is no output schema, so the description carries the full burden of explaining return values—and it does so thoroughly: findings packet fields, citations, gaps[], contradictions[], hop field, and semantic excerpting. It also covers auth prerequisites, depth differences, latency, and when not to use the tool. An agent has everything needed to select, invoke, and interpret the results 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?

The schema already covers both parameters at 100% coverage, and the description adds meaningful context on top: it explains the depth enum in operational terms (quick=3 facets single-hop, standard=3 with gap recovery, thorough=6 with iterative chasing) and clarifies that the question parameter is intended for broad/multi-part queries. This adds practical semantics beyond the per-value schema text.

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 1497 STRUCTURED data sources... in ONE call' and immediately distinguishes itself from open-web search and from sibling ask_pipeworx (single lookup vs. multi-facet research). It also explains the decomposition and parallel-tool behavior, leaving no ambiguity about what the tool does.

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?

Explicitly states when to use it: 'Best for broad/multi-part questions over structured data,' and when not to: 'For a single lookup use ask_pipeworx' and 'For BREAKING or colloquial CURRENT-NEWS... prefer ask_pipeworx.' It also names the account-requirement fallback ('If you are not signed in, use ask_pipeworx instead'). This is exemplary routing guidance with named alternatives.

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