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

Annotations already indicate readOnly, openWorld, idempotent, and non-destructive. The description adds substantial context beyond those: account requirements, parallel decomposition, findings packet structure with gaps[] and contradictions[], semantic excerpting, latency estimates, and citation_uri conditions. 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 every sentence adds distinct value: account constraints, tool scope, decomposition mechanics, return format, gap handling, citation guarantees, and latency. It is front-loaded with the account warning and immediately differentiates from siblings. It is dense rather than redundant, though slightly verbose.

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 no output schema, the description thoroughly covers input expectations, output structure (findings packet, gaps[], contradictions[], hop, citation_uri), performance expectations, edge cases (unsupported topics, large records), and prerequisites (account, paid tier). An agent has everything needed to invoke and interpret results 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 baseline is 3, but the description adds meaningful depth beyond the schema: it explains what each depth level does in terms of hops, gap recovery, and contradiction pass, and clarifies that 'question' can be broad/multi-part. This goes beyond the schema's description of the depth parameter.

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 and resource: 'Grounded multi-source research across Pipeworx's 1497 STRUCTURED data sources' in one call, and explicitly distinguishes itself from open-web search and from ask_pipeworx. It names what it is and is not, making the tool's function unmistakable even among many 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 and when-not-to-use guidance: best for broad/multi-part questions over structured data, for single lookups use ask_pipeworx, for breaking current-news prefer ask_pipeworx, and if not signed in use ask_pipeworx. It also explains how depth levels map to use cases, leaving no ambiguity about alternatives.

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