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

Even with readOnly/openWorld/idempotent annotations already present, the description adds substantial behavioral context: account/paywall requirements, expected latency (15-60s, thorough ~90s), gap reporting instead of inventing answers, fetchable citation_uri only when resolvable, contradictions[] for standard/thorough, and semantic excerpting behavior. None of this contradicts 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 operational constraint (ACCOUNT REQUIRED) and the core purpose before diving into mechanics. It is long, but the length is justified by the tool's complexity and by genuinely useful details (gaps[], citation fetchability, latency, excerpting), so it is appropriately sized rather than padded.

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?

For a 2-parameter tool with no output schema, the description is exceptionally complete: it covers authentication, pricing, latency, alternatives, return packet shape (with verbatim evidence/confidence/source/fetched_at/citations), failure semantics (gaps[]), and depth-level behavior. An agent has enough to decide, call, and interpret results without opening other docs.

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, but the description adds meaning beyond the schema: it explains what each depth level costs in terms of hops and paid status, clarifies 'quick=3 (single hop)' behavior, and links depth to gap recovery/contradictions. This enriches the enum semantics without redundancy.

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 1500 structured data sources, decomposing questions into facets and routing to 5,743 tools in parallel. It explicitly distinguishes itself from open-web search and from sibling ask_pipeworx ('this is NOT open-web search', 'For a single lookup use ask_pipeworx'). This makes its purpose 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?

It gives explicit when-to-use guidance ('Best for broad/multi-part questions over structured data') and when-not-to-use guidance ('For a single lookup use ask_pipeworx'; 'For BREAKING or colloquial CURRENT-NEWS ... prefer ask_pipeworx'). It also names the alternative (ask_pipeworx) and explains why, so an agent can route correctly.

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