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

Annotations already mark the tool as read-only, open-world, and idempotent, and the description adds substantial context: account/auth requirements, explicit gaps[] with never-invented behavior, contradiction passes, fetchable citation URIs, semantic excerpting, and latency expectations. No contradiction exists between description and 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 long but information-dense and front-loaded with the account requirement, clear operation definition, and alternatives. Some redundancy exists: 'use ask_pipeworx' appears twice and depth details overlap with the schema, which keeps it from a perfect score.

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?

For a complex tool with no output schema, the description covers input semantics, output packet contents, gaps/contradictions, auth, latency, citation fetchability, and what makes this different from alternatives. An agent has enough context to invoke it correctly and interpret results.

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% and already documents both parameters, including depth semantics. The description adds some extra meaning beyond the schema — practical question examples, timing expectations, paid-plan constraint for thorough, and citation/hop behavior — but it also repeats much of the schema's depth detail, so it earns slightly above baseline.

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 tools in parallel. It also explicitly distinguishes itself from open-web search and ask_pipeworx, so an agent can tell it apart from siblings.

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 provides explicit when-to-use guidance (broad/multi-part questions over structured data), explicit exclusions (single lookup → use ask_pipeworx), and auth-gated routing (not signed in → use ask_pipeworx). It also notes the paid tier requirement for thorough depth, leaving no ambiguity.

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