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

Annotations already declare the tool read-only, idempotent, and non-destructive, and the description adds substantial context beyond those flags: account requirements, paid-plan gating for thorough depth, parallel facet decomposition, findings-packet structure, gaps[] behavior, contradiction scanning, semantic excerpting, and expected latency. No statement contradicts 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 dense and front-loaded with the account prerequisite and core identity, and nearly every clause contributes a distinct fact. It is longer and more run-on than ideal, but the complexity of the tool justifies the length.

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?

The description covers selection criteria, prerequisites, latency, return contract, failure semantics, and depth-dependent behaviors. Because there is no output schema, the description carries the full burden of explaining what the agent will receive, and it does so thoroughly with concrete field names and citation semantics.

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. The description adds value by revealing that 'thorough' requires a paid plan and clarifying how depth choices affect hop behavior and contradiction scanning, which the schema's enum descriptions do not fully convey. This is a meaningful supplement rather than a repetition.

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 clearly states the core function: grounded multi-source research across Pipeworx's 1517 structured data sources, and explicitly contrasts itself with open-web search. It also gives concrete best-fit examples, such as comparing entities' regulatory and financial exposure, which prevents confusion with sibling tools like ask_pipeworx.

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: 'Best for broad/multi-part questions over structured data' and 'For a single lookup use ask_pipeworx instead.' It also handles the auth edge case by directing unsigned-in users to ask_pipeworx and explains the depth options and their behavioral implications. There is no ambiguity about when to select this tool.

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