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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses parallel facet routing, findings-packet contents, citation_uri conditions, gaps that are never invented, contradictions on standard/thorough, semantic excerpting of large records, and expected latency of 15-90s. It also reveals the account/paid-plan prerequisite. No claim 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 well-structured: account requirement and fallback come first, then core mechanism, output contract, best-for guidance, and edge-case behaviors. It loses a point for the duplicated 'For a single lookup use ask_pipeworx instead' sentence and some dense parenthetical overload, but nearly every item carries distinct operational value.

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?

Even without an output schema, the description specifies the return contract sufficiently: verbatim evidence, confidence, source, fetched_at, stable citations, gaps[], contradictions[], hop, and citation_uri conditions. It also covers prerequisites, latency, and boundary cases such as 'this is NOT open-web search.'

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?

Although the schema already describes both parameters, the description adds meaningful operational semantics: question broadness is the intended use case, and depth modes are tied to hop behavior, gap recovery, contradiction scans, paid tier, and latency. The depth:'thorough' paid-plan warning is useful even before an agent reads the schema.

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 identifies a resource-specific action: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources... in ONE call.' It also distinguishes itself from open-web search and from ask_pipeworx, and the example questions ('compare X and Y's regulatory + financial exposure') make the intended scope unmistakable.

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 tells the agent when not to use the tool: 'If you are not signed in, use ask_pipeworx instead' and 'For a single lookup use ask_pipeworx instead.' It also states that the tool is best for broad/multi-part questions over structured data, and flags the paid-plan requirement for the thorough depth mode.

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