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, so the bar is lower, but the description still adds substantial behavioral context: account requirements, paid depth tier, parallel decomposition, gap recovery, contradictions[] scanning, semantic excerpting, stable fetchable citations, and expected latency. No contradiction with the annotations 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 long, but it is dense with high-value information and is front-loaded with the most operationally important constraint: account requirement and the fallback tool. Every clause adds either a capability, a limitation, a routing rule, or expected output behavior. Slightly sprawling, but the structure and information-to-noise ratio are strong.

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?

Given the tool has no output schema, the description carries the full burden of explaining what the agent will receive: a findings packet with verbatim evidence, confidence, source, fetched_at, citations, explicit gaps[], contradictions[], and the 'hop' field. It also covers cost/tier, timing, and failure semantics. This is a complete operational picture for a complex tool.

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, but the description adds real meaning beyond the schema: it maps 'quick/standard/thorough' to hop counts, whether a gap-recovery/contradiction pass runs, and the paid requirement for 'thorough'. It also clarifies that 'question' is meant to be broad/multi-part because decomposition is the point. This goes beyond the bare schema definitions.

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+resource: 'grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources' in one call. It explicitly differentiates itself from siblings by saying 'this is NOT open-web search' and by directing single-lookup users to ask_pipeworx. The decomposition + parallel routing behavior makes the tool's purpose unmistakable.

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 gives explicit when-to-use guidance ('Best for broad/multi-part questions over structured data') and explicit when-not-to-use guidance ('For a single lookup use ask_pipeworx instead'). It also names the alternative for unauthenticated users ('If you are not signed in, use ask_pipeworx instead'). This is exceptionally clear routing.

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