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

Annotations already declare read-only, idempotent, non-destructive behavior, and the description adds substantial beyond-that context: parallel tool routing, never-invents gaps[], second-hop iteration, contradictions[] for standard/thorough, provenance fields per finding, semantic excerpting, auth requirements, and expected latency. No contradiction with annotations 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 long and dense, but nearly every sentence earns its place given the tool's complexity, auth nuances, mode differences, and alternatives. It is front-loaded with the account requirement and core purpose, though it reads as one continuous block and could benefit from paragraph breaks or bullets.

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?

The description covers purpose, alternatives, auth, output shape (findings packet with evidence, confidence, source, fetched_at, citation_uri, gaps[], contradictions[], hop), limitations, latency, and depth semantics. There is no output schema, so this textual detail is essential and fully supplied.

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 adds real value by explaining what question breadth means, giving concrete examples, and detailing the depth enum's hop behavior and paid-plan requirement. It clarifies that broad/multi-part questions are encouraged and that depth:'thorough' costs extra, going well beyond enum labels.

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 verb and resource: grounded multi-source research across 1,497 structured data sources, decomposing questions into facets and returning a findings packet. It also explicitly contrasts itself with open-web search and with ask_pipeworx, so an agent can distinguish it from siblings without inspecting schemas.

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 criteria: best for broad/multi-part structured-data questions, use ask_pipeworx for single lookups, prefer ask_pipeworx for breaking or colloquial current-news topics, and use ask_pipeworx when not signed in. It also states depth-specific behavior and account requirements.

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