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

The description goes far beyond the readOnlyHint/openWorldHint/idempotentHint annotations: it details the findings packet structure, explicit gaps[] for unanswered facets, contradictions[] for standard/thorough, fetchable citation_uri guarantees, semantic excerpting, and latency expectations. Nothing in the description 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 long but appropriate for a multi-faceted research tool with no output schema; it fronts the most important operational constraints (account requirement, alternative tool, latency). It loses a point because some depth details are repeated nearly verbatim from the schema, making it slightly less economical than ideal.

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 tool with no output schema and complex behavior, the description is unusually complete: it covers authentication, pricing, when to use alternatives, output contents, citation behavior, gap/contradiction handling, excerpting, and expected latency. An agent has enough context to invoke it correctly and interpret its 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?

The input schema already provides 100% coverage and rich descriptions for both question and depth, including hop counts, defaults, and the paid threshold. The description mostly restates this depth information rather than adding meaningful new parameter-level semantics, so the baseline of 3 applies.

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 identifies the tool as 'grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources' and contrasts it with open-web search. It also distinguishes itself from ask_pipeworx by noting that deep_research is for broad/multi-part questions while a single lookup should use 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?

It explicitly states when to use ask_pipeworx instead (unsigned-in users and single lookups), and when deep_research is appropriate (broad/multi-part structured-data questions). It also discloses that 'thorough' depth requires a paid plan, giving the agent actionable routing and authentication guidance.

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