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

Descriptions adds details beyond annotations: 'Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count). Cached 5min-1h depending on window.' This informs about data source, privacy, caching behavior. Annotations already cover safety, but description enriches transparency.

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?

Every sentence adds value. Front-loaded with core output, then use cases, then technical details. No fluff.

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, description explains returned fields (top tools, top packs, total call volume) and covers caching, data source, privacy. Complete for a simple read-only 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 coverage is 100% and enum values are listed. Description adds semantic context: 'Shorter windows surface what's hot right now; longer windows show steady-state demand.' This helps agents choose appropriately.

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 it returns 'top tools, top packs, and total call volume' over a time window, using specific verbs like 'Returns' and 'Discovering'. It distinguishes from sibling 'discover_tools' by focusing on trending/call volume rather than static 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?

Three explicit use cases are listed, giving clear context for when to use the tool. However, it does not explicitly state when not to use it or compare to alternatives like 'discover_tools'.

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