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

Given annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false, the description adds valuable context: it is self-aggregating, derived from CF analytics-engine, contains no PII, and is cached 5min-1h. This goes beyond the safety profile provided by 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 front-loaded with the core functionality in the first sentence, followed by bullet-point use cases and technical details. It is concise without being terse, though could potentially shorten the use-case list without losing clarity.

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?

Despite lacking an output schema, the description explains the return format (top tools, top packs, total call volume, with tuple (pack, tool, count)) and caching behavior. This provides sufficient context for an agent to understand what the tool returns and its freshness characteristics.

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% with a description for the 'window' parameter. The description adds semantic guidance on window choice ('hot right now' vs 'steady-state demand'), which helps the agent select the appropriate value beyond the enum options.

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 it returns 'top tools, top packs, and total call volume' over a recent window, using a specific verb ('Returns') and resource ('Pipeworx trending data'). It distinguishes from sibling tools like 'discover_tools' by focusing on trending aggregates rather than listing all tools.

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 lists three explicit use cases (discovering hot data sources, confirming canonical choice, checking alignment). It also explains window selection trade-offs ('Shorter windows surface what's hot right now; longer windows show steady-state demand'). However, it does not explicitly state when not to use the tool or suggest alternatives.

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