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

The description goes far beyond the annotations. It discloses account/gating requirements, parallel facet decomposition, the findings packet structure (verbatim evidence + confidence + source + fetched_at + citation), explicit gaps[] (never invented), contradictions[] for standard/thorough, the hop field, citation_uri fetchability guarantee, semantic excerpting behavior, and latency expectations. This is a thorough behavioral contract that no annotation captures.

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 front-loaded with the most critical constraint (account required) and primary alternative (ask_pipeworx). Every sentence carries operational value—limitations, output contract, depth semantics, citation guarantees. It is dense and could be tightened (minor repetition of ask_pipeworx and gaps[]), but for a tool with no output schema, the detail is justified and highly usable.

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 tool with no output schema, the description carries the full burden of explaining return values and behavior. It covers prerequisites, when/when-not, parameter semantics, output format, error-gap behavior, citation semantics, contradictions, excerpting, and latency. Nothing an agent needs to decide whether to call it or to interpret its response 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 baseline is 3. The description adds meaning beyond the schema: it explains the tier gating on depth ('thorough' needs paid plan), behavioral differences between depth values (gap recovery for standard, lead-chasing for thorough), timing implications, and that question is meant to accommodate broad/multi-part queries. This enriches both parameters beyond their enum/type definitions.

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 is exceptionally clear: it names the verb (research/decompose/routes/returns), the specific resource (1497 STRUCTURED data sources), and the multi-tool parallel execution model. It explicitly distinguishes itself from ask_pipeworx (single lookup) and states 'this is NOT open-web search,' so an agent can separate it from siblings without opening schemas.

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?

Usage guidance is explicit and actionable: 'Best for broad/multi-part questions over structured data,' 'For a single lookup use ask_pipeworx,' 'For BREAKING or colloquial CURRENT-NEWS... prefer ask_pipeworx,' and 'If you are not signed in, use ask_pipeworx instead.' It names alternatives and gives concrete conditions for choosing them, including failure modes (empty gaps[] for non-catalog topics).

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