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

The description goes well beyond the readOnly/openWorld/idempotent annotations by disclosing decomposition behavior, parallel routing to 5,798 tools, gap[] semantics ('never invented'), hop/contradictions fields, citation fetchability guarantees, semantic excerpting, and expected latency ranges. Nothing 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 information-dense; it front-loads the critical account requirement and immediately gives a fallback. Every sentence adds a distinct behavioral fact (routing, evidence fields, gaps, contradictions, excerpting, latency). Only minor redundancy—'in ONE call' and 'one LLM call' could be trimmed—but the structure is still purposeful.

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 tool with only 2 simple params, no output schema, and rich annotations, the description fully covers what an agent needs: when to use it, what to expect back, how to handle gaps, latency, auth, and sibling routing. No critical missing context.

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 documents both parameters. The description does add useful real-world meaning for the depth enum (explains hop behavior and paid tier for thorough) and for the question parameter (broad/multi-part is fine), but it doesn't fundamentally need to compensate for a schema gap, so a baseline-3 is appropriate.

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-resource pair ('multi-source research across Pipeworx's 1517 structured data sources') and clearly differentiates from sibling tools like ask_pipeworx and open-web search. It also explains the output shape (findings packet with evidence, confidence, source, fetched_at, citation) and gives concrete example questions.

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?

Explicitly says when to use this tool vs alternatives: 'best for broad/multi-part questions over structured data', 'for a single lookup use ask_pipeworx', and 'for breaking/current news prefer ask_pipeworx'. It also states the account/payment prerequisite and what depth levels are for.

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