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 that: account and paid-tier requirements, parallel decomposition into facets, explicit gaps[] for unanswered parts, never-invented evidence, contradictions[], fetchable citation URIs, semantic excerpting, and latency expectations. No contradiction with annotations exists.

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 and front-loaded with the account warning and the key alternative tool. Every section delivers useful information, but there is mild redundancy: the 'one call' promise appears in multiple places and citation fetchability is stated more than once. A slightly tighter structure would reach 5.

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?

Because there is no output schema, the description correctly carries the burden of describing return values: findings packet with verbatim evidence, confidence, source, fetched_at, stable citation, gaps[], and contradictions[]. It also covers auth, paid plans, latency, and alternatives. Nothing an agent needs to select and invoke this tool correctly 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 description coverage is 100%, so the baseline is 3. The description adds real value beyond the schema by explaining that 'thorough' requires a paid plan, characterizing the hop behavior for quick vs standard vs thorough, and providing example question shapes. It does not fully redefine the parameters because the schema already does that well, but it enriches the operational meaning.

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 and resource: grounded multi-source research across Pipeworx's 1517 structured data sources, with concrete domains like SEC filings, FRED/BLS, FDA, USPTO, markets, and science. It also explicitly contrasts with open-web search and with the sibling ask_pipeworx, so an agent can clearly tell this tool 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?

Usage guidance is explicit and actionable: 'Best for broad/multi-part questions over structured data', 'For a single lookup use ask_pipeworx', and 'If you are not signed in, use ask_pipeworx instead'. This names the alternative, the condition for choosing it, and the auth prerequisite.

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