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

Even with strong readOnly/openWorld/idempotent/non-destructive annotations, the description adds substantial behavioral context: it produces a findings packet with verbatim evidence, confidence, source, fetched_at, pipeworx:// citations, gaps[], contradictions[], and never invents answers. It also discloses auth requirements, paid-tier limits, citation fetchability guarantees, semantic excerpting, and expected latency.

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 account requirement and the alternative tool, and nearly every sentence adds useful behavior. However, it is overly long and contains redundant guidance such as the repeated 'For a single lookup use ask_pipeworx instead' and depth-mode details already present in the schema, which hurts conciseness.

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?

With no output schema present, the description carries the full burden of explaining return values, and it does so thoroughly: findings packet fields, gaps[], contradictions[], hop field, citation_uri, semantic excerpting, latency, auth, and depth behavior. For a research tool of this complexity, no critical invocation or interpretation information appears to be missing.

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% and the schema already documents both parameters in detail, including depth facet counts, iteration hops, and the paid requirement. The description adds latency expectations and examples, but it mostly restates the schema rather than providing new parameter syntax or deeper field semantics.

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 states a specific verb and resource: grounded multi-source research across Pipeworx's 1,517 structured data sources, decomposing a question into facets and routing them across 5,798 tools in parallel. It also differentiates itself from open-web search and from ask_pipeworx, which makes the tool easy to pick out among 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?

The description explicitly says when to use it: 'Best for broad/multi-part questions over structured data' and gives example queries. It also explicitly names the alternative and the condition to choose it: 'For a single lookup use ask_pipeworx instead' and 'If you are not signed in, use ask_pipeworx instead'.

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