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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description goes well beyond these by explaining decomposition into facets, parallel routing across 5,798 tools, the findings packet structure (verbatim evidence, confidence, source, fetched_at, pipeworx:// citation), explicit gaps[] for unanswered facets, contradictions[] for standard/thorough, semantic excerpting of large records, and expected latency. This is rich, non-redundant behavioral disclosure.

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 every section carries useful information: account requirement, alternative tool, core behavior, ideal use cases, depth semantics, citation behavior, and timing. It is front-loaded with the most critical invocation constraint. Slightly verbose in places, but structure and density justify the length for a complex tool.

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 full responsibility for describing return values. It does so thoroughly: findings packet fields, gaps[], contradictions[], hop field, citation_uri fetchability, and semantic excerpting. It also covers prerequisites, alternatives, depth options, and latency, so an agent has complete context for calling the 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 meaning beyond the schema by noting that depth:'thorough' requires a paid plan and by clarifying time expectations for each depth tier. The schema already describes quick/standard/thorough mechanics, so the incremental value is moderate but real.

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 uses a specific verb and resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources' in 'ONE call', and explicitly contrasts with 'NOT open-web search.' It also differentiates from siblings by stating it is best for broad/multi-part questions and pointing to ask_pipeworx for single lookups, so an agent can reliably select this over alternatives.

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 is explicit about when to use this tool versus alternatives: 'Best for broad/multi-part questions over structured data', and 'For a single lookup use ask_pipeworx instead.' It also gives a clear fallback: if not signed in, use ask_pipeworx. This removes guesswork about invocation conditions.

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