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

The description substantially exceeds the annotations by disclosing account/auth prerequisites, the findings packet structure, explicit gaps[] for unanswered facets, contradictions[] scans for standard/thorough, semantic excerpting of large records, and expected latency. All of this is consistent with the readOnly, openWorld, idempotent, and non-destructive 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 densely informative; it front-loads the critical account gate and alternative tool before diving into mechanics, then covers return structure, depth semantics, and latency. Minor redundancy exists (ask_pipeworx is named as fallback twice) and the prose is dense, but the length is justified for a complex tool with no output schema.

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?

Despite having no output schema, the description fully specifies what the agent will receive: a findings packet with verbatim evidence, confidence, source, fetched_at, citation_uri/hop, gaps[], contradictions[], and excerpting details. It also covers prerequisites, alternatives, depth behavior, and timing, so an agent has everything needed to invoke and interpret the tool correctly.

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 schema already fully documents both question and depth, including the depth enum, defaults, paid tier, hops, gap recovery, and contradictions. The description mostly restates this behavior in prose rather than adding new parameter-level constraints; only the example research questions and account gating go slightly beyond the schema, which is not enough to lift it above baseline.

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 precise verb and resource: it performs grounded multi-source research across 1,517 structured data sources in one call, decomposing the question into facets and routing them to tools in parallel. It also explicitly distinguishes itself from ask_pipeworx and from open-web search, so an agent can tell it apart from sibling tools.

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 gives explicit when-to-use guidance: best for broad/multi-part questions over structured data, with concrete examples, and explicitly says to use ask_pipeworx for a single lookup or when not signed in. It also flags the paid-plan requirement for the thorough depth, leaving no ambiguity about the appropriate alternative.

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