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

Annotations already mark it read-only, idempotent, non-destructive, and open-world; the description adds substantial context beyond that: account/pricing prerequisite, latency expectations (15-60s, ~90s for thorough), return-packet structure (verbatim evidence, confidence, source, fetched_at, pipeworx:// citation), the gaps[] never-invented guarantee, contradictions[] behavior, hop/citation_uri semantics, and semantic excerpting. No contradiction with 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 with value but organized as a wall of text, jumping between account status, mechanism, examples, depth semantics, citation guarantees, excerpting, and latency. The ask_pipeworx contrast and depth-tier behavior each appear in more than one place, creating redundancy. For a tool this complex, length is justified, but tighter paragraphing and deduplication would improve it.

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 no output schema, the description fully explains return values (findings packet fields, gaps[], contradictions[], hop, citation_uri), prerequisites (account, paid tier), latency, alternative routing, and edge-case behavior (empty gaps when the topic isn't catalogued). For a complex tool with only 2 parameters, nothing an agent needs to call it correctly 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 meaning beyond the schema: it explains what each depth tier behaviorally buys (gap-recovery hop, lead-chasing, contradictions scan, latency, paid requirement) and gives question-parameter guidance via examples. Some schema content is restated, which keeps it from a 5, but it genuinely enriches the depth enum 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 verb and resource: "Grounded multi-source research across Pipeworx's 1500 STRUCTURED data sources ... in ONE call." It explicitly differentiates itself from open-web search ("this is NOT open-web search") and from the sibling ask_pipeworx by naming it and describing what it does instead. An agent can confidently distinguish this tool from its siblings without opening any other definition.

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 and when-not guidance: "If you are not signed in, use ask_pipeworx instead," "Best for broad/multi-part questions over structured data," and "For a single lookup use ask_pipeworx." It even predicts failure mode ("deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog"), so the agent knows not to use it for news or open-web topics.

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