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

Annotations already cover safety (readOnly, idempotent, non-destructive), and the description goes well beyond them: auth/gating (free tier, thorough needs paid plan), latency (15-60s, thorough ~90s), the gaps[] honesty guarantee ("never invented"), citation resolvability semantics (citation_uri only present when fetchable), contradictions[] behavior, and semantic excerpting of large records. No contradiction with annotations — the openWorldHint aligns with the candid note that gaps[] appear when a topic is not in the structured catalog.

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 (~280 words) but the tool is genuinely complex, and each sentence carries distinct information: auth gate, sibling routing, core mechanism, output packet, use-cases, exclusions, depth behaviors, citation semantics, latency. It is front-loaded with the most act_ion-relevant gate (auth requirement) before the core function. Minor deduction for re-explaining the depth enum semantics that the schema already covers in detail.

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 values — and it does: findings packet fields (verbatim evidence, confidence, source, fetched_at, pipeworx:// citation), gaps[], contradictions[], hop field, and citation_uri semantics. Combined with auth, latency, and 34-sibling routing guidance, everything an agent needs to invoke this tool correctly is present.

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 description coverage is 100% and the depth enum is already well-documented (quick=3, standard=3 with gap recovery, thorough=6 paid). The description adds genuine value on top: concrete example questions for the question param, per-depth latency implications, and operat_ional notes on what depth changes in behavior. It does not fully re-explain the schema but complements it — solidly above the baseline 3.

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 states a specific verb and resource — "Grounded multi-source research across Pipeworx's 1506 STRUCTURED data sources" — and sharply distinguishes itself from open-web search ("this is NOT open-web search") and from the sibling ask_pipeworx. Concrete example queries ("compare X and Y's regulatory + financial exposure") anchor what the tool is for, so an agent can tell it apart from the 34 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?

Provides explicit when-to-use and when-not-to-use guidance: best for broad/multi-part structured-data questions; for a single lookup, for breaking current-news topics, or when not signed in, use ask_pipeworx instead. It even names the fallback condition (not signed in) and the alternative tool by name, leaving nothing to inference.

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