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

Annotations already declare readOnlyHint/openWorldHint/idempotentHint and no destructive behavior, and the description adds substantial behavioral context beyond that: account/paid-plan requirements, parallel decomposition across 5,798 tools, the findings packet structure, explicit gaps[] rather than invented answers, contradictions[], citation fetchability, excerpting of large records, and expected latency. No annotation contradiction 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 long, but every sentence earns its place given the tool's complexity and the absence of an output schema. It front-loads the critical account requirement, then moves through behavior, return packet contents, depth semantics, caveats, and latency in a logical flow.

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 and a complex tool, the description fully carries the burden of explaining what the agent will receive: findings with verbatim evidence, confidence, source, fetched_at, citations, gaps[], contradictions[], excerpting, and timing. It also covers the depth variants and their distinct behaviors, making the tool callable correctly without further lookup.

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. The description adds value beyond the schema by clarifying that 'question' can be broad/multi-part, that 'thorough' requires a paid plan, and by explaining how depth choices affect hops, gap recovery, and contradiction scanning. This is meaningful but not exhaustive beyond the already-rich schema descriptions.

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, decomposing questions and returning a findings packet. It also explicitly distinguishes itself from open-web search and from ask_pipeworx, making sibling differentiation clear.

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 selection guidance: use ask_pipeworx if not signed in, use ask_pipeworx for a single lookup, and use deep_research for broad/multi-part structured-data questions. It also explains behavior across depth levels, so an agent can choose the right mode.

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