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

Annotations already mark readOnlyHint, openWorldHint, idempotentHint, destructiveHint. The description adds context: 'Self-aggregating signal — derived from CF analytics-engine, no PII' and 'Cached 5min-1h depending on window.' This discloses data source, privacy, and caching behavior, adding significant value beyond 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 well-structured with numbered use cases and concise sentences. Every sentence adds value, and there is no redundancy. The length is appropriate for the complexity of the tool.

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 no output schema, the description explains the return: 'top tools, top packs, and total call volume.' It also mentions caching behavior. Given the tool's simplicity (single optional parameter), the description is complete and sufficient for an agent to invoke it 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?

The schema already has 100% coverage with an enum and description. The description adds: 'Shorter windows surface what's hot right now; longer windows show steady-state demand.' This provides additional guidance for parameter selection, justifying a score above the baseline of 3.

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 purpose: returns top tools, top packs, and total call volume. It lists three specific use cases, making it easy to understand when to use it. The description distinguishes this analytics tool from sibling tools like ask_pipeworx or discover_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 explicitly lists three useful scenarios (discovering hot data sources, confirming canonical tools, aligning use cases). While it does not mention when not to use it, the context is clear enough to guide agent selection. No direct alternatives are named, but the use cases are specific.

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