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

Beyond the annotations (readOnly, openWorld, idempotent, non-destructive), the description adds rich behavioral context: it is self-aggregating, derived from CF analytics-engine, contains no PII, and is cached 5min-1h depending on window. This informs the agent about data freshness and privacy, exceeding what annotations alone provide.

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 front-loaded with the main purpose, followed by a concise list of use cases and a brief technical note. It is slightly longer than strictly necessary but every sentence adds value. The structure is logical and easy to scan, though the use-case list could be tightened.

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?

Given the tool's simplicity (one optional parameter, no output schema), the description is complete: it explains what is returned, the available windows, caching behavior, and data privacy. There is no missing information that an agent would need to decide whether and how to call this 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 only parameter 'window' has full schema coverage with its enum and basic description. The tool description adds extra semantic value by explaining that shorter windows surface what's hot right now while longer windows show steady-state demand, which helps the agent choose appropriately. This goes beyond the schema's simple enum listing.

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 states what the tool does: it returns the top tools, top packs, and total call volume over a recent window. The verb 'Returns' is specific, and the resource is well-defined. It also distinguishes itself from siblings like discover_tools by focusing on what other AI agents are calling on Pipeworx, making it unique.

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 provides explicit use cases: discovering hot data sources, confirming canonical tool choices, and checking alignment with agent behavior. It also explains how to choose the window parameter based on needs (shorter for hot right now, longer for steady-state demand), offering clear guidance on when to use this tool.

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