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

The annotations already declare read-only, open-world, and idempotent behavior, and the description adds far more: explicit gaps[] instead of invented answers, fetchable citation_uri semantics, contradictions[] for standard/thorough, semantic excerpting rather than head-truncation, and expected latency. This thoroughly sets agent expectations beyond what annotations provide.

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 the critical account prerequisite front-loaded, followed by purpose, alternatives, depth behavior, output details, and timing. Every sentence earns its place and the length is justified by the tool's complexity.

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?

There is no output schema, so the description's detailed return-packet explanation is essential and sufficient: evidence, confidence, source, fetched_at, citation_uri, gaps, contradictions, and hop semantics. It also covers authentication, cost, alternative tools, and latency, leaving no critical gap for an agent deciding whether and how to call it.

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 concrete question examples, paid-plan implications for thorough depth, and latency expectations. However, some depth behavior details are already well documented in the schema, so the description adds moderate rather than extensive new 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 action—grounded multi-source research across 1,517 structured data sources—and clearly distinguishes it from open-web search and from the ask_pipeworx sibling. It also gives concrete output contents and examples, so an agent can tell exactly what deep_research does.

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?

It explicitly says when to use this tool: broad/multi-part questions over structured data, with single lookups routed to ask_pipeworx instead. It also handles the account prerequisite by directing unsigned-in users to ask_pipeworx, giving concrete routing rules rather than vague guidance.

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