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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint: false. The description adds valuable behavioral detail: it never invents missing answers, returns explicit gaps[], provides stable and fetchable citations, semantically excerpts large records, and gives realistic latency expectations. There is no contradiction with 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 dense and quite long, but nearly every sentence carries operational weight: auth, source scope, alternatives, decomposition, output shape, behavior on gaps, and latency. It is front-loaded with the critical account requirement and then builds to use-case guidance. A slightly tighter structure would help, but there is little waste.

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?

There is no output schema, so the description fully compensates by describing the findings packet fields, the explicit gaps[] behavior, contradictions for standard/thorough, citation stability, and expected wait times. It also covers auth and plan requirements, making it complete enough for an agent to select and invoke the tool 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 at 100% coverage, giving the baseline of 3. The description adds useful extra context around the depth parameter, such as latency differences and the paid requirement for 'thorough', and reinforces that the question should be natural language and broad.

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 specific verb and resource: it runs grounded multi-source research across Pipeworx's 1540 structured data sources. It clearly separates itself from open-web search and says it is for broad/multi-part questions, distinguishing it from sibling lookup tools.

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 to use ask_pipeworx when not signed in and for single lookups, and says deep_research is best for broad/multi-part questions over structured data. It also states the paid-plan boundary for the 'thorough' depth, giving clear when-to-use and when-not-to-use guidance.

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