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

The annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, and the description adds substantial context beyond those: it never invents findings, returns explicit gaps[], describes depth-dependent contradiction scanning, explains the stable pipeworx:// citation behavior, and discloses expected latency. No contradiction with 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 front-loaded with the most critical operational detail (account requirement) and the sibling alternative. Every paragraph earns its place by covering prerequisites, use cases, output structure, depth semantics, citation guarantees, and latency. It is dense rather than redundant, though slightly sprawling due to asides and parentheticals.

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 present, the description carries the burden of explaining return values, and it does so thoroughly: findings packet with verbatim evidence, confidence, source, fetched_at, citation_uri, gaps[], contradictions[], hop field, and the guarantee that citations are fetchable. It also covers account/paywall constraints and latency expectations, making the tool safely invokable without additional lookups.

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% for both parameters, so the baseline is 3. The description adds useful semantic context beyond the schema, such as 'thorough' requiring a paid plan, the gap-recovery difference between standard and thorough, and the contradiction scan behavior. It reinforces the natural-language flexibility of the question parameter with examples.

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 clear verb and resource: deep_research conducts 'grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources' in one call. It explicitly distinguishes itself from open-web search and mentions ask_pipeworx as the alternative for cases like signed-out users or single lookups, which differentiates it 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 explicitly says when to use this tool ('Best for broad/multi-part questions over structured data') and when not to use it ('If you are not signed in, use ask_pipeworx instead'; 'For a single lookup use ask_pipeworx instead'). This is clear routing guidance with named alternatives and conditions.

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