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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, and the description adds substantial context: account requirements, paid plan for 'thorough', latency expectations, gaps[] for unanswered facets, 'never invented' evidence, semantic excerpting, and resolvable citation_uri. There is no contradiction between the description and 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 every sentence carries operational value: account requirements, alternatives, output packet structure, gaps behavior, latency, citation fetchability, and excerpting strategy. It is front-loaded with the most critical selection constraint (account required / use ask_pipeworx) and avoids fluff.

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?

For a tool with no output schema, the description thoroughly covers return shape (findings packet with evidence, confidence, source, fetched_at, citation), failure behavior (gaps[], contradictions[]), latency expectations, and depth-specific behavior. An agent has enough context to decide when to call it and to interpret its 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%, so the baseline is 3. The description adds little beyond the schema for either parameter: the depth semantics are already fully detailed in the enum descriptions, and the 'question' guidance ('Broad/multi-part is fine — decomposition is the point') is essentially repeated verbatim in the schema. The description does not provide meaningful extra parameter-level meaning.

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 1500 STRUCTURED data sources.' It explicitly differentiates from siblings by saying 'this is NOT open-web search' and by contrasting with ask_pipeworx for single lookups. An agent can clearly understand what deep_research does and how it differs from nearby tools.

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.' It also names alternatives and conditions: 'For a single lookup use ask_pipeworx', 'For BREAKING or colloquial CURRENT-NEWS ... prefer ask_pipeworx', and 'If you are not signed in, use ask_pipeworx instead.' This leaves little room for mis-selection.

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