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

The description goes far beyond the annotations by explaining decomposition, parallel routing, return packet contents, explicit gaps[], contradiction[], hop fields, citation_uri fetchability, semantic excerpting, latency expectations, and plan-based depth behaviors. It also discloses that citations are only included when actually fetchable, which is useful behavioral context.

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?

Although long, the description is front-loaded with the most critical operational constraint (account requirement and fallback) and every subsequent sentence adds useful information about selection, behavior, output, or limitations. No filler or tautology.

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 covering return fields, citation behavior, gap handling, contradiction reporting, latency, authentication, and alternatives. Given the tool's complexity, nothing essential is missing for an agent to select and invoke it 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?

The schema already documents both parameters fully at 100% coverage, so the baseline is 3. The description adds meaning by explaining what each depth level actually does (standard gap recovery, thorough multi-hop and contradictions scan), that thorough requires a paid plan, and expected latency implications.

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 that deep_research performs 'Grounded multi-source research across Pipeworx's 1500 STRUCTURED data sources' in a single call, and explicitly distinguishes itself from open-web search. It also identifies the sibling ask_pipeworx for single-lookup cases, so an agent can tell which tool fits.

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: if not signed in, use ask_pipeworx instead; deep_research is best for broad/multi-part structured-data questions; and for a single lookup, prefer ask_pipeworx because deep_research returns mostly empty gaps for topics outside its structured catalog. This gives clear when-to-use and when-not-to-use direction.

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