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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, and the description adds substantial behavioral context beyond those: account and paid-plan requirements, parallel routing across 5,743 tools, gap[] behavior, no-invention guarantees, hop fields, citation_uri resolvability, contradictions[], semantic excerpting, and expected latency. No contradiction with the annotations is present.

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 and dense, but nearly every sentence contributes a distinct fact about behavior, prerequisites, output, or usage boundaries. It is front-loaded with the account requirement, which is operationally critical, then proceeds through core behavior and limitations. It could be more scannable with headings, but it is information-dense without filler.

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 so thoroughly: findings packet, verbatim evidence, confidence, source, fetched_at, citation_uri, gaps[], contradictions[], and hop field. It also covers prerequisites, latency, scope boundaries, multi-step resolution, and semantic excerpting. For a tool of this complexity, nothing an agent needs to select and invoke it 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 coverage is 100%, so the baseline is 3, but the description adds valuable parameter-level meaning beyond the schema: it links depth levels to account tier, latency expectations, and behavioral outcomes like gap recovery and contradiction scans. The question parameter is contextualized as accepting decomposition-friendly natural language. Some depth-enum explanation repeats the schema, but the extra operational context justifies a point above baseline.

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 clearly identifies a specific verb and resource: grounded multi-source research across Pipeworx's structured data sources, explicitly contrasting itself with open-web search. It also distinguishes itself from ask_pipeworx by describing its decomposition and parallel tool-routing behavior. The name and title are far less informative than the description, which fully establishes what the tool uniquely does.

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, while single lookups and breaking/current-news topics should go to ask_pipeworx. It also names an account prerequisite and an alternative path for unsigned-in users. The sibling contrast is concrete and actionable, not merely implied.

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