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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses the auth/paid-plan requirement, parallel decomposition, gaps[] with never-invented guarantee, stable and fetchable citation_uri, contradictions[] for standard/thorough, semantic excerpting, and expected latency. These are meaningful behavioral traits not captured by 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?

Despite being long, the description is front-loaded with the most critical constraints (account requirement, alternative tool) before core mechanics, and every sentence adds a distinct fact: access, scope, routing, return format, gap handling, contradictions, latency. There is no filler; the density is justified by the tool's complexity.

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 carries the burden of explaining return values, and it does so in detail: findings packet contents, hop field, citation_uri, gaps[], contradictions[], and latency. Combined with the rich annotations and complete parameter schema, no critical calling information is missing.

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 schema already documents question and depth. The description adds operational meaning beyond the schema: 'thorough' requires a paid plan, depth choices affect hop behavior and latency, and multi-step questions resolve in one call. It improves parameter understanding without being redundant.

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 names a concrete operation—grounded multi-source research over Pipeworx's 1517 structured data sources in one call—and immediately distinguishes itself from open-web search and ask_pipeworx for single lookups. 'NOT open-web search' and 'For a single lookup use ask_pipeworx instead' make sibling differentiation explicit.

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 when-to-use guidance ('Best for broad/multi-part questions over structured data') and when-not-to ('For a single lookup use ask_pipeworx instead'), plus an auth-based fallback to ask_pipeworx for unsigned users. This leaves no ambiguity about selecting the tool.

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