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

The description discloses key behaviors beyond the annotations: it is not open-web search, it may return gaps for topics outside the structured catalog, it requires an account and a paid plan for thorough depth, and it provides fetchable citation URIs. These details align with the readOnly/openWorld/idempotent annotations and give the agent realistic expectations about outputs and limitations.

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 front-loaded with the primary purpose and usage guidance, but it is quite verbose and includes some redundant emphasis ('IN PARALLEL', 'NOT open-web search', 'never invented'). However, the extra detail is mostly functional and relevant to an agent deciding whether and how to invoke the tool.

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 what the tool returns. It covers the findings packet structure, contradictions, gaps, hop fields, citation_uri resolvability, semantic excerpting, and expected timing, which is sufficient for an agent to understand the tool's behavior and results.

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% and the description adds substantial meaning beyond the schema. It explains what kind of natural-language question to provide and gives a detailed breakdown of the depth enum values, including hop behavior, gap recovery, contradiction scanning, and expected latency.

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 deep_research as a grounded multi-source research tool over Pipeworx's structured data catalog, and explicitly distinguishes it from ask_pipeworx and open-web search. It states the specific verb ('research'), the resource (1517 structured data sources), and the intended use case (broad/multi-part questions).

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: prefer deep_research for broad/multi-part structured-data questions, prefer ask_pipeworx for single lookups and for breaking/current news topics. It also explains the depth levels and how second-hop iteration works, so an agent can choose the right mode and know when to route elsewhere.

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