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

The annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior, and the description enriches this with substantial context: it never invents answers, returns explicit gaps[], flags contradictions[], provides stable pipeworx:// citations, semantically excerpts large records, and discloses latency ranges. This goes well beyond the annotations and gives the agent accurate expectations for invocation and result interpretation.

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 well organized: account requirements and alternatives come first, then the core function, then output format, fidelity guarantees, and latency. Every major sentence adds behavioral or routing value, though some of the depth-mode explanation overlaps with the schema's already-detailed enum description.

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 research tool with no output schema, the description is remarkably complete: it covers prerequisites, tier restrictions, fallback routing, scope, decomposition method, result packet content, gap handling, contradiction detection, citation resolvability, large-record behavior, and expected latency. An agent has enough information to select the tool, set parameters correctly, and interpret the response.

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%, so the schema fully documents both 'question' and 'depth'. The description repeats much of the depth behavior already present in the schema, but does add the paid-tier note for 'thorough' and reinforces that broad/multi-part questions are acceptable. This is baseline-appropriate: the schema carries the heavy lifting and the description adds only marginal semantics.

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 over 1,517 structured data sources in one call. It explicitly distinguishes itself from open-web search and names the sibling tool for single lookups. An agent can clearly tell what this tool does and how it differs from related 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?

The description gives explicit when-to-use guidance: best for broad/multi-part questions over structured data, and for a single lookup use ask_pipeworx instead. It also provides a fallback instruction for unsigned-in users: use ask_pipeworx. It names alternatives and conditions directly without leaving inference to the agent.

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