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

The annotations already mark the tool as read-only, non-destructive, idempotent, and open-world. The description adds substantial behavioral context beyond those hints: it returns a findings packet with evidence, confidence, source, fetched_at, and pipeworx:// citations; it emits explicit gaps[] for unanswered facets and never invents findings; it semantically excerpts large records; it reports typical latency; and it exposes the hop-based recovery and contradictions behavior for standard/thorough depths. No statement contradicts 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 but front-loaded with the most decision-critical facts: account requirement, fallback tool, and structured-data scope. Every sentence adds substantive information for a complex tool, though some depth details duplicate what the input schema already documents. It is dense rather than rambling, so the length is justified.

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?

Despite having no output schema, the description fully explains the return shape, the limitations (gaps[], contradictions[], empty results for topics outside the catalog), citation resolvability, excerpting behavior, and latency. It covers prerequisites, alternatives, usage conditions, and behavioral semantics, leaving essentially nothing an agent needs to decide whether and how to invoke the tool.

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 already documents both parameters clearly. The description adds useful semantic context beyond the schema, including the paid-plan requirement for depth:'thorough', the behavioral difference between standard and thorough hops, the gap-recovery/contradictions behavior, and expected latency. It does not fully re-explain each depth option, which is appropriate given the schema's thorough parameter descriptions.

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 ('research') and resource ('Pipeworx's 1497 STRUCTURED data sources'), and clearly differentiates itself from open-web search and from ask_pipeworx. It states the tool decomposes questions into facets and routes them in parallel, so an agent can tell exactly what this tool does and how it differs from siblings.

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 selection criteria: use for broad/multi-part questions over structured data; use ask_pipeworx for a single lookup or for breaking/current-news topics. It also states that if not signed in, ask_pipeworx should be used instead, and notes depth:'thorough' requires a paid plan. This is exemplary when-to-use guidance with named alternatives.

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