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

Annotations already mark this as readOnly, openWorld, idempotent, and non-destructive. The description adds valuable context beyond those hints: account/sign-in requirements, paid-plan gating for 'thorough,' parallel decomposition behavior, second-hop gap recovery, contradiction scanning, explicit gaps[] instead of fabrication, and a citation_uri that is only emitted when actually resolvable. This is exactly the kind of contextual disclosure the dimension asks for, with no contradiction against 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 but every section earns its place: auth upfront, core mechanism, use-case examples, depth behavior, output guarantees, and latency. It is front-loaded with the most decision-relevant constraints. It loses one point because it runs together as a long, parenthetical-heavy paragraph; bullet points or clearer section breaks would make the same information significantly easier to scan.

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?

There is no output schema, so the description carries the full burden of explaining return values — and it does: findings packet, verbatim evidence, confidence, source, fetched_at, stable pipeworx:// citation, gaps[], contradictions[], hop field, and citation_uri semantics. Combined with the rich annotations and full schema coverage, an agent has everything needed to select, invoke, and interpret results correctly.

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 schema already fully documents both parameters, including depth values ('quick=3', 'standard=3', 'thorough=6') and the hop/recovery/contradiction behavior. The prose description mostly restates or contextualizes that information rather than adding new per-parameter semantics, so the high-coverage baseline of 3 is appropriate.

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 operation: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources ... in ONE call,' then details exactly how it works (decomposes into facets, routes to 5,798 tools in parallel, returns a findings packet). It also distinguishes itself from open-web search and from ask_pipeworx for single lookups, so an agent can clearly tell it apart from sibling tools.

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?

The description gives explicit when-to-use guidance: 'Best for broad/multi-part questions over structured data' with concrete examples. It gives explicit when-not-to-use guidance: 'For a single lookup use ask_pipeworx instead' and 'If you are not signed in, use ask_pipeworx instead.' It also explains depth-level trade-offs and that 'thorough' requires a paid plan, leaving no ambiguity about selection.

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