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

Annotations already mark the tool read-only/idempotent, and the description matches them while adding substantial runtime behavior: account/plan requirements, gap[] plus contradictions[] output, hop recovery, semantic excerpting, citation resolvability, and latency expectations. There is no contradiction between the description and the readOnlyHint/openWorldHint 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 dense and front-loaded with the most critical operational fact (account requirement) before the capability summary. It is unusually long, and a few points could be tightened, but the length is largely justified by the tool's complexity and the absence of an output schema.

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 full burden of explaining return shape, and it does: findings packet, evidence, confidence, source, fetched_at, pipeworx:// citations, gaps[], contradictions[], and hop fields. Auth, payment, latency, scope limits, and alternative tools are all covered, leaving no critical calling decision unresolved.

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?

The input schema already gives full coverage for both parameters, so the baseline bar is met. The description goes beyond it by clarifying what kind of question fits ('broad/multi-part is fine — decomposition is the point') and by adding operational meaning to depth (paid tier, ~90s, iterative hops), which helps an agent choose values.

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 and resource: 'Grounded multi-source research across Pipeworx's 1495 STRUCTURED data sources' in one parallel call, and explicitly contrasts itself with open-web search and with ask_pipeworx. The 'best for broad/multi-part questions over structured data' phrase makes the tool's role unmistakable even without opening the schema.

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 concrete when-to-use guidance with named alternatives: use ask_pipeworx when signed out, for single lookups, and for breaking/colloquial current-news topics. It also states the condition under which deep_research fails (non-structured topics) and explains which depth to choose, so an agent can route correctly.

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