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

With readOnlyHint=true and idempotentHint=true, the description still adds substantial behavioral context: auth/plan requirements, disambiguation from open-web search, the findings-packet structure (verbatim evidence, confidence, source, fetched_at, stable citation), explicit gaps[] for unanswered facets, 'never invented', contradictions[] for standard/thorough, hop field, citation_uri resolvability, semantic excerpting, and 15-90s latency. Nothing contradicts 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 but every sentence earns its place: auth/alternative up front, then core mechanism, output format, depth semantics, and latency. It is well-structured and front-loaded, with only minor redundancy against the schema's depth description.

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?

This is a complex research-orchestration tool with no output schema, so the description must fully explain return values and behavior. It does: findings packet contents, gaps[], contradictions[], hop field, citation_uri, semantic excerpting, latency expectations, and auth prerequisites. An agent can correctly invoke it and interpret its results without further lookup.

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 per the rubric baseline is 3. The description adds a little nuance beyond the schema ('Broad/multi-part is fine — decomposition is the point' for question, and depth-behavior details around hops and contradictions), but it mostly restates what the schema already documents for depth and doesn't substantially add 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 1496 STRUCTURED data sources' and details the mechanism ('Decomposes your question into focused facets, routes each to the right one of 5,718 tools IN PARALLEL, and returns a findings packet'). It also distinguishes itself from open-web search and from ask_pipeworx, so an agent can clearly tell it apart from siblings.

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?

Explicit when-to-use and alternative guidance: 'If you are not signed in, use ask_pipeworx instead — it works on every tier' and 'Best for broad/multi-part questions over structured data... For a single lookup use ask_pipeworx.' It also explains the paid-plan condition for thorough depth, leaving no ambiguity about prerequisites or choice.

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