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

Annotations already mark the call read-only/idempotent; the description adds substantial behavior: account/paid-plan requirement, gaps[] with never-invented findings, stable fetchable citation_uri, contradictions[] for standard/thorough, semantic excerpting rather than head-truncation, and 15-90s latency. No contradiction with the 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 and dense, but nearly every clause carries operational value (auth, exclusions, depth behavior, citation guarantees, latency). It is somewhat monolithic as a single paragraph and repeats a little of the depth schema, so it is not maximally concise, though the information is well ordered.

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?

Despite having no output schema, the description enumerates the returned findings packet (verbatim evidence, confidence, source, fetched_at, citation_uri, gaps[], contradictions[], hop) and covers auth, latency, and sibling routing. An agent has what it needs to decide, call, and interpret the result.

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%, but the description still adds semantics: question is explicitly allowed to be broad/multi-part because decomposition is the point, and depth behavioral differences are tied to second-hop iteration, gap recovery, contradiction scans, and the paid plan for thorough. This goes well beyond the enum descriptions in the schema.

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?

States a specific verb and resource: 'Grounded multi-source research across Pipeworx's 1540 STRUCTURED data sources' in one call, decomposing into facets and routing to tools. It explicitly distinguishes itself from open-web search and from ask_pipeworx, so an agent can tell what deep_research is and is not without opening the schema.

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?

Gives explicit when-to-use guidance ('Best for broad/multi-part questions over structured data') and when-not-to-use guidance with named alternatives ('For a single lookup use ask_pipeworx'; 'For current events ... prefer ask_pipeworx'; 'If you are not signed in, use ask_pipeworx instead'). Also explains which depth values suit iterative gap-recovery needs.

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