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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses account and paid-plan requirements, expected latency (15-60s, up to ~90s), gap[] and contradiction[] behaviors, citation URI resolvability, and semantic excerpting. This is rich behavioral context that significantly exceeds the annotation coverage, with no contradiction.

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 front-loaded with the critical account requirement and alternative tool, then moves from core behavior to usage to deep mechanics. However, it repeats the depth enum semantics already present in the schema and is longer than strictly necessary for a two-parameter tool.

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 compensates by spelling out the findings packet structure: verbatim evidence, confidence, source, fetched_at, citation, gaps[], and contradictions[]. It also covers latency, account requirements, citation fetchability, and excerpting behavior, making it complete for correct invocation and result interpretation.

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%, so the schema documents both parameters. The description adds operational meaning: examples of good research questions, the pricing/latency implications of the depth enum, and how depth levels affect hop and contradiction behavior—extending beyond the schema without contradicting it.

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 a specific resource and action: grounded multi-source research across 1,517 structured data sources, decomposing questions into facets and routing to 5,798 tools in parallel. It explicitly distinguishes itself from open-web search and from the sibling ask_pipeworx for single lookups.

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 gives explicit when-to-use guidance ('best for broad/multi-part questions over structured data') and when-not-to-use guidance ('for a single lookup use ask_pipeworx instead'). It also names the alternative for unsigned-in users, so an agent knows exactly which sibling to select.

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