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

Annotations already provide readOnly/openWorld/idempotent/destructive hints, and the description adds a wealth of context beyond them: account and paid-plan gating, exact return packet shape (verbatim evidence, confidence, source, fetched_at, citation), the gaps[] never-invented policy, hop/citation_uri resolvability, contradictions[] on standard/thorough, semantic excerpting behavior, and latency expectations. 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 front-loaded with the most critical gate ('ACCOUNT REQUIRED') and the core non-obvious fact ('this is NOT open-web search'). Every sentence carries distinct, actionable information, so the length is justified for a tool of this complexity. It loses a point for being a single dense wall of text that would benefit from section breaks or bullets for scannability.

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 complex tool with no output schema, the description covers everything needed to invoke it correctly: authentication/paywall constraints, return format, gap/contradiction behavior, depth semantics, latency, and clear routing to ask_pipeworx for the cases it cannot handle. No essential operational detail 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 meaningful extra semantics for both parameters. It clarifies that `question` can be broad and multi-part, and it defines each `depth` value behaviorally (quick=3 facets, standard=gap recovery+contradictions, thorough=6 facets+leads+contradictions) and notes the paid-tier requirement for `thorough`. This goes beyond the schema's one-line enum descriptions.

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 ('research'), a precise resource ('Pipeworx's 1500 STRUCTURED data sources'), and explicitly distinguishes itself from both open-web search and sibling ask_pipeworx. The opening line 'this is NOT open-web search' plus the contrast with ask_pipeworx lets an agent immediately place the tool.

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 guidance ('Best for broad/multi-part questions over structured data'), when-not-to-use ('For a single lookup use ask_pipeworx'), and a definitive alternative for current-news topics ('prefer ask_pipeworx'). Also provides an authentication-related rule: if not signed in, use ask_pipeworx. Nothing is left to inference.

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