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

Beyond the annotations, the description discloses parallel decomposition, routing to thousands of tools, the findings packet structure, gaps[] for unanswered facets, no invention of data, stable citations, semantic excerpting, contradictions[] behavior, and latency expectations. It adds rich behavioral context and does not contradict the readOnly/openWorld/idempotent hints.

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 front-loaded and dense: it leads with account requirements and the fallback tool, then core behavior, use cases, output details, and timing. Every sentence carries distinct information needed for correct invocation and sibling selection.

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 compensates by explaining the findings packet contents, gaps[], contradictions[], citation format, excerpting behavior, latency, and authentication constraints. An agent has sufficient context to invoke the tool and interpret its results 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. The description adds value with the paid-plan requirement for thorough, expected latency ranges, and clarifying that broad/multi-part questions are appropriate, though much of the depth parameter's semantics already appear in the schema.

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 precisely identifies the tool as grounded multi-source research over Pipeworx's structured data sources in one call, and explicitly contrasts it with open-web search. It also distinguishes itself from ask_pipeworx for single lookups, making the scope and resource crystal clear.

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 gives explicit routing instructions: use ask_pipeworx when not signed in or for a single lookup, and states that the thorough depth requires a paid plan. It also provides concrete best-fit scenarios with examples, so an agent knows exactly when to select this tool over siblings.

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