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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered structurally. The description adds genuinely new behavioral insight: parallel decomposition into facets, verbatim evidence + confidence + source, gaps[] for unanswered facets, contradictions[] on certain depths, semantic excerpting, expected 15-90s latency, and the caveat that citations are only present when the source record is actually fetchable. That is substantial value beyond 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 dense and front-loaded with the most critical caveat (account required; fallback). But it is long and somewhat rambling — a paragraph of caveats and clarifications that could be tightened. It earns its place for the most part, but loses a point to over-length and occasional redundancy (e.g., explaining 'NOT open-web search' twice in different words).

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?

Context is complex: a paid-tier gating constraint, a clear fallback alternative, latency expectations, output shape (findings packet with gaps, contradictions, citation URIs), and critical failure semantics (empty gaps[] when topic isn't in catalog). The description addresses all of these. The only notable gap is that it never explicitly states that 'quick' skips the contradictions[] scan — implied by the depth parameter description but not spelled out in the main description. Given the output schema is absent, the description still does enough to let an agent call it 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%, and the description adds enrichments: it explains what 'quick/standard/thorough' actually do in behavioral terms (gap recovery, contradiction scan, paid tier) and clarifies that 'question' can be broad/multi-part. However, much of this repeats or closely restates what the parameter descriptions already provide. The baseline of 3 is appropriate since the schema already carries the load.

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 ('researches'), a precise resource (Pipeworx's 1500 structured data sources), and clarifies a critical boundary — this is 'NOT open-web search.' It also names the key distinction from the closest sibling (ask_pipeworx), so an agent can discriminate without opening schemas.

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 ('best for broad/multi-part questions over structured data'), explicit when-not-to-use ('single lookup', 'BREAKING or colloquial CURRENT-NEWS' — prefer ask_pipeworx), and even names the alternative tool. That satisfies the full usage-guidance test.

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