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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint. Description adds caching behavior (5min-1h), data source (CF analytics-engine), and privacy (no PII), which are valuable 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?

Description is three sentences plus a bullet list, all front-loaded. Every sentence adds information—no redundancy or filler words.

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 read-only analytics tool, the description covers its function, parameters, caching, and privacy. Lacks output schema details (e.g., structure of top tools/packs), but is still adequate given simplicity.

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 covers 100% with enum and description. Description adds semantic guidance: 'Shorter windows surface what's hot right now; longer windows show steady-state demand,' enhancing the parameter's meaning.

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 states it returns 'top tools, top packs, and total call volume over a recent window,' using specific verb–resource mapping. It distinguishes from sibling tools like ask_pipeworx and discover_tools by focusing on trending analytics rather than direct Q&A or general discovery.

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 (hot data sources, canonical tool confirmation, alignment check). While no 'when not to use' is given, the clarity of use cases combined with sibling context provides adequate guidance.

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