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

Despite readOnlyHint=true already signaling safety, the description adds rich behavioral detail: parallel routing, a findings packet with verbatim evidence + confidence + source + fetched_at, gaps[] for unanswered facets, never-invented claims, contradictions[] for standard/thorough, semantic excerpting of large records, and the condition that citation_uri is only present when fetchable. It also explains the multi-hop behavior of depth tiers, well beyond what annotations provide.

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 front-loads the most critical information (account requirement and alternative tool) before the mechanism. It is longer than typical, but nearly every sentence carries essential guidance. A small deduction for a garbled stretch in the middle and slight redundancy in the depth explanation.

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, the description compensates thoroughly: it describes the findings packet structure, citation semantics, gaps[] and contradictions[] behavior, latency expectations, and the account/paid-tier prerequisite. For a tool of this complexity with two parameters and rich behavior, nothing an agent needs to know before invoking is missing.

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 baseline is 3, but the description adds major value: it translates the depth enum values into concrete behavioral differences (quick=3 facets single-hop, standard=3 facets with gap-recovery, thorough=6 facets paid with iterative chasing), and clarifies that the question parameter is meant for broad, multi-part natural-language queries. The one minor glitch in the middle of the description doesn't negate the strong parameter guidance.

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 identifies the tool's function: grounded multi-source research across 1,517 structured data sources, decomposing questions into facets and routing them in parallel to 5,798 tools. It explicitly calls out what it is NOT ('this is NOT open-web search') and distinguishes it from ask_pipeworx, making both purpose and differentiation unambiguous.

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 states exactly when to use the tool ('best for broad/multi-part questions over structured data'), provides concrete sample questions, and gives an explicit alternative with a condition: 'If you are not signed in, use ask_pipeworx instead.' It also specifies depth tiers and expected latency, giving an agent full guidance on selection.

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