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

Annotations already mark the tool as read-only, open-world, and idempotent, but the description adds substantial behavioral context beyond that: account and plan requirements, expected latency (15-60s, up to ~90s for thorough), the explicit gaps[] behavior with 'never invented' assurance, contradictions[] output, semantically excerpted records rather than head-truncation, and the guarantee that citation URIs are always fetchable. This richly discloses side effects, limitations, and output semantics.

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 densely packed with relevant information and well-ordered: account requirements first, then the core capability, then selection guidance, then depth semantics, then output details, then latency. Almost every sentence adds value for correct tool invocation. It loses one point for length and some redundancy around gap/contradiction behavior, but overall it is structured and purposeful.

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 tool with two parameters, no output schema, and non-trivial behavior, the description covers everything an agent needs: authentication prerequisites, tier-based depth limitations, expected response shape (findings packet with evidence/confidence/source/fetched_at/citation URI), edge-case behavior (gaps[], contradictions[], never-invented), performance expectations, and alternatives. There is no substantial missing context.

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?

Although the schema already documents both parameters fully (100% coverage), the description adds significant meaning: it explains what each depth value does operationally (quick=single hop, standard=gap-recovery hop + contradictions, thorough=iterative hop + lead chasing), clarifies that 'thorough' requires a paid plan, and notes that multi-part questions are encouraged because decomposition is the point. This goes well beyond the schema's terse 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 very specific action: grounded multi-source research across 1,500 structured data sources, decomposed into facets and routed in parallel to 5,743 tools. It explicitly contrasts itself with open-web search and distinguishes itself from ask_pipeworx ('For a single lookup use ask_pipeworx instead'), so there is no ambiguity about what this tool does versus its siblings.

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?

The description provides explicit when-to-use and when-not-to-use guidance: sign-in requirement ('If you are not signed in, use ask_pipeworx instead'), the 'thorough' paid plan condition, and a clear best-fit scenario ('Best for broad/multi-part questions over structured data'). It also names the alternative for single lookups, making routing decisions fully explicit.

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