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

Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint), the description discloses critical behavioral details: data provenance ('derived from CF analytics-engine'), privacy ('no PII'), output shape ('just (pack, tool, count)'), and caching ('Cached 5min-1h depending on window'). This gives the agent realistic expectations about data freshness and content.

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 tightly structured: a lead sentence stating what it does, a summary of output, and a numbered list of use cases. Every sentence adds value and there is no redundant filler, making it easy for an agent to parse quickly.

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 simple read-only tool with one optional parameter, the description fully covers the output contents, data source, privacy, and caching behavior. Since the return shape is described in plain terms ('top tools, top packs, and total call volume'), the absence of an output schema does not leave a gap.

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 schema already documents the single `window` parameter with an enum and a rich description (100% coverage). The tool description only briefly references the window options and adds minimal new parameter semantics, as the schema's parameter description already covers the trade-offs between shorter and longer windows.

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 the tool's function: 'Returns the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d)'. It uses a specific verb ('Returns') and identifies the exact resource, distinguishing it from sibling tools by focusing on aggregate AI-agent usage rather than individual lookups.

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 three explicit 'Useful for' scenarios, giving the agent clear guidance on when to invoke this tool: discovering hot data sources, confirming canonical tool choice, and aligning with typical agent needs. However, it does not explicitly mention sibling alternatives or state when not to use it.

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