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

Annotations already declare readOnly/openWorld/idempotent, and the description adds substantial context beyond them: account requirements and paid plan for 'thorough', latency expectations (15-60s, up to ~90s), the never-invented gap[] behavior, contradictions[] for standard/thorough, fetchable citation_uri semantics, and semantic excerpting of large records. 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 information-dense and front-loaded with the most critical constraint (ACCOUNT REQUIRED). It earns nearly every sentence, but there is minor redundancy: the advice to use ask_pipeworx '— it works on every tier' appears twice, and the depth behavior partially mirrors schema text.

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?

Despite having no output schema, the description fully explains the return packet (verbatim evidence + confidence + source + fetched_at + pipeworx:// citation, gaps[], contradictions[], hop field), auth requirements, latency, and how citations are guaranteed fetchable. For a complex multi-source research tool, nothing an agent needs to invoke it correctly is missing.

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 description coverage is 100%, so the baseline is 3. The description adds meaning by giving example questions for the 'question' parameter ('compare X and Y's regulatory + financial exposure') and clarifying that multi-step questions resolve in one call, which goes slightly beyond the schema's 'Broad/multi-part is fine'. The depth parameter details mostly restate the schema's already-rich enum description, with the paid-plan note repeated.

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?

States a specific verb and resource: 'Grounded multi-source research across Pipeworx's 1500 STRUCTURED data sources... in ONE call', then details facet decomposition and parallel routing to 5,743 tools. Explicitly distinguishes itself from open-web search and from the sibling ask_pipeworx by naming it as the single-lookup alternative.

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?

Gives explicit when-to-use and when-not-to-use guidance: 'Best for broad/multi-part questions over structured data', 'For a single lookup use ask_pipeworx instead', and 'If you are not signed in, use ask_pipeworx instead'. Provides concrete example questions that an agent can pattern-match against.

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