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

Annotations (readOnlyHint, openWorldHint, idempotentHint) already signal a safe non-mutating external lookup, and the description adds substantial context beyond them: findings are 'never invented' with explicit gaps[], citation_uri is present 'only when the source emits one that resources/read can actually serve', large records are semantically excerpted 'not head-truncated', standard/thorough return contradictions[], and latency is disclosed (15-60s, up to ~90s). No contradiction with the annotation hints.

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 (~350 words) but dense, and the most critical operational constraints — account required, paid tier for 'thorough', and the sibling fallback — are front-loaded before any feature description. Each block (scope, depth mechanics, citation guarantees, latency) earns its place, though there is minor redundancy where the prose depth explanation overlaps the schema's depth field description and the 'not open-web / not for news' point is made twice.

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 composition, gaps[], contradictions[], hop, citation URI guarantees, and excerpting behavior are all covered. Prerequisites (account, paid tier), exclusions, depth-specific behavior, and latency are also present — nothing an agent needs to decide whether to call it or what to expect back 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% and the depth enum is already well-documented in the schema, so the baseline is 3. The description adds genuine value on top: it explains what each depth tier does behaviorally (gap recovery, lead-chasing, contradictions scan) and ties tiers to latency expectations, plus it reinforces question semantics with broad/multi-part examples. No parameter meaning is left to guesswork.

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+resource: 'Grounded multi-source research across Pipeworx's 1499 STRUCTURED data sources... in ONE call', which clearly identifies what the tool does. It distinguishes itself from siblings by explicitly warning 'this is NOT open-web search' and naming ask_pipeworx as the alternative for single lookups, so an agent can differentiate it from the 30+ siblings immediately.

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?

Explicitly scopes when to use it — 'Best for broad/multi-part questions over structured data' with two concrete examples — and when not to: 'For a single lookup use ask_pipeworx', 'deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog', and 'If you are not signed in, use ask_pipeworx instead'. It names the alternative sibling and the exact conditions that select it.

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