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

Annotations already declare read-only, open-world, idempotent, and non-destructive traits. The description adds useful context beyond annotations: it mentions caching behavior (5min-1h), data provenance (CF analytics-engine), and privacy (no PII). This enriches the agent's understanding of what to expect. No contradiction with 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 appropriately sized—a single-purpose tool with one optional parameter gets a dense but not bloated description. It front-loads the core function, then lists use cases and operational details. Every sentence contributes; no redundancy. Slightly long but justified by the useful context.

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 and no output schema, the description is remarkably complete. It explains what is returned, window options and their implications, caching behavior, data source, and privacy. The annotations cover safety, so this description fully equips an agent to select and invoke the 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?

With 100% schema description coverage, the baseline is 3. The description adds value by explaining how the window parameter affects results ('Shorter windows surface what's hot right now; longer windows show steady-state demand'). This goes beyond the schema's simple enum listing, helping the agent choose appropriate values.

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 what the tool does: it returns top tools, top packs, and total call volume over a recent window. The verb 'Returns' plus the specific resource (top tools/packs/call volume) makes the purpose explicit. It also distinguishes itself from siblings by focusing on trending/aggregate agent behavior rather than individual 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?

The description lists three concrete use cases: discovering hot data sources for current events, confirming a popular tool is canonical, and seeing alignment with agent needs. This provides clear context for when to use the tool. However, it does not explicitly mention alternatives or when not to use it, so it falls short of a 5.

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