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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses important behavioral details: parallel facet routing, explicit gaps[] for unanswered facets, citations only when fetchable, contradictions[] for standard/thorough modes, semantic excerpting of large records, and expected latency. These details add substantial context without contradicting 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?

Although long, the description is dense and front-loaded: it starts with the account requirement and alternative tool, then covers scope, method, output packet, depth variants, citation guarantees, and timing. Each sentence contributes distinct operational or selection-relevant information.

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 provided, the description carries the burden of explaining return values and does so thoroughly: findings packet contents, gap recovery, contradictions[], hop field, citation_uri behavior, and latency expectations are all covered. Account and pricing constraints are also included, so an agent has enough information to decide whether and how to invoke the tool.

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?

The input schema already documents both parameters at 100% coverage, but the description adds significant meaning: depth modes are explained in terms of hops, gap recovery, contradiction scans, and paid tiers. It also reinforces that the question parameter is meant to accept broad, multi-part natural language queries.

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 the tool as grounded multi-source research over Pipeworx's 1,517 structured data sources, with question decomposition and parallel routing to 5,798 tools. It explicitly distinguishes itself from open-web search and from ask_pipeworx, making its purpose unambiguous relative to 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 gives explicit when-to-use guidance: it is 'best for broad/multi-part questions over structured data' and provides concrete examples. It also states exclusions and alternatives: '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.