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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, but the description adds substantial behavioral context: it never invents answers, returns gaps[], citations are stable and fetchable, standard/thorough add recovery hops and contradiction scans, and expected latency is stated. This goes well beyond what structured annotations alone communicate.

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 but well-organized and front-loaded with the critical authentication gate before usage details. It loses a point for redundancy: the pipeworx:// citation statement appears twice, and the free/paid/account messaging is repeated at both the beginning and the end.

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?

For a complex, multi-hop research tool with no output schema, this description is remarkably complete. It covers the data sources, the parallel decomposition behavior, the shape of the findings packet, gaps[], contradictions[], depth semantics, auth requirements, paid plan implications, and latency expectations. An agent has everything needed to decide whether and how to invoke it.

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 baseline is 3, and the schema already explains depth tiers in detail. The description adds extra semantics such as the paid requirement for thorough, quick being the minimum, higher concurrency on paid plans, and the research credit billing model, which helps an agent choose the right depth value.

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 1506 STRUCTURED data sources' in ONE call. It also explicitly distinguishes itself with 'this is NOT open-web search' and contrasts with ask_pipeworx, so an agent can immediately tell this tool apart from its siblings.

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 also gives clear when-not-to-use direction: 'For a single lookup use ask_pipeworx instead' and 'If you are not signed in, use ask_pipeworx instead'. This is exemplary routing information.

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