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

Beyond the annotations (readOnly, openWorld, idempotent, non-destructive), the description discloses the multi-tool parallel decomposition, the findings packet structure, gaps[] for unanswered facets, contradictions[] for deeper depths, citation_uri resolvability, semantic excerpting, never-invented grounding, latency expectations, and paid-tier behavior. This is exceptionally rich behavioral context.

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 dense with necessary operational details: auth, alternatives, output contents, timing, and limitations. It front-loads the account requirement and sibling fallback, which is the most decision-critical information. A minor deduction only because some clauses could be tightened without losing meaning.

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 complex tool with no output schema, the description carries the full burden of explaining return shape, behavior, prerequisites, limitations, latency, and route-to-alternatives. It covers all of these thoroughly, including concrete example questions and what happens when the catalog lacks the topic.

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, but the description adds meaningful depth: it explains the practical effect of depth values (gap-recovery hop, follow-up leads, contradictions scan, paid requirement for thorough) and how question broadness maps to the tool's decomposition behavior. This goes beyond the schema's bare enum descriptions.

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 1497 STRUCTURED data sources... in ONE call'. It immediately differentiates itself from open-web search and from sibling ask_pipeworx, so an agent can tell exactly what this tool does and does not do.

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 when-not-to-use guidance is provided: use for broad/multi-part structured-data questions; use ask_pipeworx for single lookups or breaking/current-news topics. It also names alternatives ('use ask_pipeworx instead') and gives the account prerequisite for signed-out users.

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