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

Despite annotations already declaring readOnly/openWorld/idempotent/non-destructive, the description adds a wealth of non-redundant behavioral context: account gating and the paid 'thorough' tier, latency expectations (15-60s, up to ~90s), the 'never invented' gap guarantee, contradictions[] behavior per depth tier, citation resolvability semantics, and semantic excerpting of large records. No statement conflicts 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 long (~350 words) but decision-critical information is front-loaded: account requirement and sibling fallback appear first, before mechanism, output format, and timing. It is dense with no filler, but loses a point for redundancy — the contradictions[] behavior is described both in the body and in the schema's depth parameter, and the citation-resolvability sentence is more verbose than necessary.

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 tool with no output schema, the description fully compensates: it specifies the return packet contents (verbatim evidence, confidence, source, fetched_at, citation, gaps[], contradictions[]), the auth and cost model, the latency envelope, the exhaustive-scope guarantee, and the fallback path. An agent has everything it needs to decide whether to invoke and how to interpret the result.

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 coverage is 100% and the schema's depth description is already rich, establishing a baseline of 3. The description adds genuine extra value: the paid-plan constraint on 'thorough' (a critical invocation gate absent from the schema) and the clarification that broad/multi-part natural-language questions are the intended input shape for the question parameter. This modest but operationally meaningful addition justifies one point above baseline.

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+resource ('multi-source research across Pipeworx's 1499 STRUCTURED data sources') and explicitly differentiates from siblings ('this is NOT open-web search', 'For a single lookup use ask_pipeworx'). It also explains the mechanism — decomposing questions into facets and routing to 5,738 tools in parallel — so an agent knows exactly what this tool is and is not.

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?

Gives explicit when-to-use ('Best for broad/multi-part questions over structured data'), explicit when-not-to ('For a single lookup use ask_pipeworx'), and a named fallback condition ('If you are not signed in, use ask_pipeworx instead — it works on every tier'). The alternative tool is named and the selection condition is unambiguous — nothing left to inference.

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