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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint. Description adds that data is derived from CF analytics-engine, no PII, and cached 5min-1h, providing context beyond annotations without contradiction.

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?

Concise, front-loaded with core purpose, then use cases, then technical details. Every sentence adds value without redundancy. Well-structured with bullet-point-like numbering for use cases.

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?

No output schema, but description adequately describes return type (top tools, top packs, total call volume). Caching and data source details provide enough context for the agent to understand behavior. Could include format hints but is sufficient for a simple trending 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?

Schema already documents the 'window' parameter with enum values and descriptions (100% coverage). The description adds semantic guidance: shorter windows show what's hot, longer windows show steady-state demand, which enhances understanding beyond schema.

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 returns top tools, top packs, and total call volume over a window. It distinguishes itself from siblings by specifying the self-aggregating signal and use cases like discovering hot data sources or confirming canonical 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?

Explicitly lists three use cases and explains window trade-offs (short vs. long). Does not mention when not to use it or offer alternatives among siblings, but the guidance is clear and actionable.

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