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

Annotations already declare readOnly/idempotent/non-destructive, but the description adds substantial behavioral context: latency expectations, depth-dependent hop behavior, gap recovery, never-invented gaps[], semantic excerpting of large records, and citation_uri only being present when resolvable. There is no contradiction with the provided 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?

The description is long but each block earns its place for a complex tool: account gate, core scope, use cases, alternatives, depth behavior, output semantics, and latency. It is somewhat dense and slightly repetitive around contradictions and citation behavior, but the information is well front-loaded and organized.

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 present, the description thoroughly explains return values: findings packet, verbatim evidence, confidence, source, fetched_at, hop, contradictions[], and the resolvable citation_uri. It also covers failure modes (gaps[]), limitations (current news), and latency. This is complete enough for an agent to invoke the tool correctly.

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 schema already documents all 9 parameters including aliases and the depth enum. The description mostly restates what the schema says about depth and aliases rather than adding new parameter-level meaning; the baseline of 3 is appropriate.

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 action — grounded multi-source research across Pipeworx's 1676 STRUCTURED data sources — and explicitly says it is NOT open-web search. It differentiates from siblings like ask_pipeworx by scope (one call, parallel decomposition) and by the shape of the result (findings packet with citations and gaps).

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?

Provides explicit when-to-use guidance: best for broad/multi-part questions over structured data. It also gives concrete when-not-to-use cases: single lookups and breaking/current-news topics should go to ask_pipeworx, and it names the alternative tool directly. The account gating instruction ('if you are not signed in, use ask_pipeworx instead') is also explicit and actionable.

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