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

Annotations already indicate read-only, open-world, idempotent, non-destructive behavior, and the description adds substantial detail beyond that: decomposition into facets, parallel routing, gap reporting, contradictions scanning, citation URIs that are always fetchable, semantic excerpting, latency, and authentication requirements. No annotation contradiction exists.

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 but every sentence carries decision-relevant information: the account gate and sibling alternative are front-loaded, then output structure, depth behavior, latency, and edge-case handling follow in a logical order. It is long because the tool is complex, not because of repetition or filler.

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?

There is no output schema, so the description carries the full burden of explaining return behavior; it does so thoroughly with fields, gaps[], contradictions[], hop, citation_uri, and fetchability guarantees. It also covers authentication, cost, alternatives, depth tiers, and expected latency, making it complete enough for an agent to select and invoke 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 description coverage is 100%, so the baseline is 3. The description adds helpful meaning by explaining the behavioral effect of depth values — standard re-angles gaps, thorough chases leads from the first pass — and by framing the question parameter as naturally multi-part, which aids correct invocation.

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 1517 structured data sources in one call. It explicitly contrasts with open-web search and with ask_pipeworx, making sibling differentiation immediate and unambiguous.

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?

Usage guidance is explicit: use this for broad/multi-part questions over structured data, and use ask_pipeworx for single lookups or when not signed in. It also names the paid tier requirement for depth:thorough, so an agent can route decisions correctly.

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