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

Annotations already mark this as read-only, idempotent, non-destructive, and open-world; the description adds substantial context on top: no invented answers, explicit gaps when facets are unanswered, contradictions scans, fetchable citation_uri only when resolvable, semantically excerpted records, and account gating. No claims contradict 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 long because the tool is complex and there is no output schema, and the most decision-relevant facts such as account requirement, alternative tool, and non-open-web behavior come first. It is a single dense paragraph with parenthetical asides, which reduces scannability, but every sentence contributes a distinct fact.

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, the description carries the full burden of explaining the return shape and it does: findings packet fields, gaps[], contradictions[], hop, citation_uri, latency, source coverage, and limitations. It also covers auth, pricing, and exclusion from open-web search; nothing an agent needs to call 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?

The input schema already covers both parameters fully, including detailed depth enum descriptions, so the baseline is 3. The description adds useful extra semantics beyond the schema: thorough requires a paid plan, depth tiers map to follow-up hops and contradictions behavior, and the expected 15-90s latency varies by depth.

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?

Description states a specific operation: grounded multi-source research across 1,517 structured data sources, decomposing a question into facets and routing to 5,798 tools in parallel. It explicitly distinguishes itself from open-web search and from the ask_pipeworx sibling, so an agent can tell what it does without opening the input schema.

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, and a single lookup should use ask_pipeworx instead. It also states account requirements, paid depth tier, and expected latency, so the agent can decide whether the tool is appropriate for a given query and user tier.

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