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

Annotations already declare read-only, open-world, and idempotent behavior; the description adds substantial extra context: account and paid-plan requirements, latency expectations, explicit gaps[] for unanswered facets ('never invented'), resolvable citation_uri guarantees, contradictions[] on deeper depths, semantic excerpting, and hop behavior. None of this 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 information-dense and front-loads the account requirement, but it is overly long and rambling, mixing account requirements, output format, sibling routing, depth semantics, citation guarantees, and latency into one wall of text. Single-lookup guidance is mentioned more than once, and some phrasing feels garbled, which hurts readability despite the rich content.

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 carries the burden of explaining return values, and it does: verbatim evidence, confidence, source, fetched_at, stable pipeworx:// citations, gaps[], contradictions[], hop field, and semantically excerpted records. It also covers account requirements, depth differences, latency, and when to prefer ask_pipeworx. Nothing essential for correct invocation 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 goes well beyond the schema. It explains depth tier implications beyond the enum ('thorough' requires paid plan), latency differences, gap-recovery and contradiction behavior, and clarifies that the question parameter can be broad and multi-part with examples. This is meaningful added semantics.

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?

States a specific purpose: 'Grounded multi-source research across Pipeworx's 1506 STRUCTURED data sources' with a clear mechanism (decompose into facets, route to tools in parallel, return a findings packet). It also explicitly says 'this is NOT open-web search' and names ask_pipeworx as the sibling for that case, so an agent can distinguish it from alternatives.

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?

Provides explicit when-to-use guidance: best for broad/multi-part questions over structured data, with concrete examples. It also gives clear when-not-to-use guidance: single lookups, timely news, and open-web topics should go to ask_pipeworx, and unsigned-in users are told to use ask_pipeworx instead. Alternatives and conditions are both named.

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