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

Annotations already declare readOnly/idempotent/openWorld, and the description still adds a large behavioral layer: account and paid-tier requirements, 15-60s/up-to-90s latency, the findings-packet shape (verbatim evidence, confidence, source, fetched_at, pipeworx:// citation), explicit gaps[] with 'never invented', contradictions[] on standard/thorough, semantic excerpting rather than head-truncation, and the guarantee that citation_uri is always fetchable. 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?

Dense and information-rich — every sentence carries unique value and the critical gate (account required + fallback tool) is front-loaded. Deduction because the prose meanders between account, purpose, best-for, not-for, depth mechanics, citation details, and latency without clear sectioning, and the opening parenthetical is overloaded with billing and signup details.

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 present, the description carries the full burden of describing return values, and it succeeds: findings-packet fields, gaps[], contradictions[], hop field, citation_uri resolvability, latency, and auth/tier gates are all covered. Nothing an agent needs to invoke or interpret this tool 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 coverage is 100%, so the baseline is 3; the description adds value beyond the schema by explaining the depth enum's behavioral consequences (gap-recovery hop for standard, lead-chasing iterative hop + paid plan for thorough, contradictions[] scan) and by framing the question parameter with examples of the broad/multi-part questions it exists for. The schema already documents the mechanics, so the description is additive rather than essential.

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 1504 STRUCTURED data sources... in ONE call' — and explicitly contrasts itself with open-web search and with ask_pipeworx. An agent can distinguish it from the research-family siblings (ask_pipeworx, compare_entities, entity_profile) without reading their 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?

Gives explicit when-to-use ('Best for broad/multi-part questions over structured data' with concrete examples), when-not-to-use ('For a single lookup use ask_pipeworx'; breaking/colloquial current news should prefer ask_pipeworx), and a hard gate ('If you are not signed in, use ask_pipeworx instead'). Alternatives are named with the exact condition that selects them.

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