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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, and the description adds substantial behavioral context on top: the account/paid-tier requirement, parallel facet decomposition across 5,798 tools, gap-recovery and contradictions[] behavior per depth level, semantic excerpting, latency expectations (15-60s, up to ~90s), and the conditional presence of citation URIs (only when resources/read can actually serve them). This richly exceeds what the annotations convey.

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 front-loaded (auth gate and routing first) and logically organized, but it is long and contains redundancy with the schema: the enum description already specifies hop counts, gap recovery, contradictions[], and per-depth behavior, which the prose re-states ('depth:"standard" re-angles unanswered gaps', 'contradictions[] scan'). Several sentences repeat information already in structured fields, which the rubric says earns no credit.

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 having no output schema, the description fully characterizes the return packet (verbatim evidence + confidence + source + fetched_at + pipeworx:// citation), explains the gaps[] behavior and the 'never invented' guarantee, covers authentication and pricing gates, names alternatives, and sets latency expectations. An agent has everything needed to decide whether and how to invoke this tool 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%, so the baseline is 3 — the schema already documents both parameters well, including the precise differences between quick/standard/thorough. The description adds value beyond the schema by coupling depth:'thorough' to the paid plan, explaining latency implications of each depth, and clarifying that the question parameter accepting multi-part queries is the intended use case ('decomposition is the point'). That added context justifies a 4.

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+resource ('Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources ... in ONE call') and explicitly contrasts itself with open-web search ('this is NOT open-web search'). It also differentiates from siblings by naming ask_pipeworx as the single-lookup alternative, so an agent can immediately tell them apart.

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 example questions, and explicit when-not-to-use rules ('For a single lookup use ask_pipeworx instead') plus an auth-based routing rule ('If you are not signed in, use ask_pipeworx instead'). No inference is required.

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