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

Annotations already declare readOnly/openWorld/idempotent/non-destructive, and the description adds substantial context beyond them: auth tier constraints, parallel decomposition to 5,798 tools, explicit gaps[] honesty guarantee ('never invented'), contradictions[] for standard/thorough, semantic excerpting of large records, fetchable citation_uri rule, and 15-90s latency expectations. These traits are disclosed with no contradiction against the 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?

Long but efficiently front-loaded: account gate and fallback tool first, then execution model, then use cases, then depth semantics, then timing. Nearly every clause earns its place, but the depth-tier behavior partially duplicates the input schema's depth parameter description, which costs a small amount of efficiency.

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 correctly carries the full burden of documenting return values: the findings packet contents (verbatim evidence, confidence, source, fetched_at), gaps[] and contradictions[] arrays, the hop field, and citation_uri fetchability. For a high-complexity tool with an enum and multi-tier behavior, this description leaves nothing an agent needs to invoke and interpret results 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 schema already documents both parameters. The description adds genuinely useful increments: the paid-plan constraint on depth:'thorough', example question phrasings, the 'single lookup' guidance that implies the question parameter shape, and latency expectations per tier. This exceeds the schema baseline of 3 without fully carrying the parameter documentation burden.

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 1517 STRUCTURED data sources... in ONE call' and explicitly contrasts with 'NOT open-web search.' It also distinguishes from the sibling ask_pipeworx by naming it as the alternative for single lookups, so an agent can select correctly without opening the schema.

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?

Gives explicit when-to-use guidance: 'Best for broad/multi-part questions over structured data' with two concrete example questions. Provides two explicit exclusions with alternatives: 'If you are not signed in, use ask_pipeworx instead — it works on every tier' and 'For a single lookup use ask_pipeworx instead.' Nothing is left to inference.

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