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

Annotations already mark the tool as read-only and idempotent, but the description adds substantial behavioral context beyond those hints: account and paid-plan requirements, parallel decomposition, findings packet contents, explicit gaps rather than invented facts, contradictions detection, latency expectations, and semantic excerpting. There is no contradiction with 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 front-loaded with the most important facts: account requirement, the alternative tool, and the core purpose. However, it is long and contains redundant points about citations and contradictions, plus a confusing parenthetical aside, so not every sentence earns its place cleanly.

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?

Even though there is no output schema, the description compensates thoroughly by describing the return packet, citation resolvability, gaps and contradictions fields, depth-specific behavior, expected latency, auth requirements, and the preferred alternative. For a complex tool with no output schema, the agent has enough to invoke and interpret the tool 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, but the description adds meaning beyond the schema: it ties the depth values to account tiers and paid plans, and frames the question parameter as best suited to broad/multi-part research while steering single lookups to ask_pipeworx. That is meaningful added value, though the schema already documents the core depth behaviors.

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, decomposing questions into facets and routing them to 5,798 tools in parallel. It also distinguishes itself from ask_pipeworx and explicitly from open-web search, so an agent can differentiate it from siblings without reading their schemas.

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?

It explicitly says when to use the tool: broad/multi-part questions over structured data. It also gives clear when-not guidance: signed-out users and single-lookup questions should use ask_pipeworx instead. Depth-level guidance is included as well, tying quick/standard/thorough to plan requirements.

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