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

Annotations already declare readOnly, openWorld, idempotent, non-destructive. The description adds valuable context: data source (CF analytics-engine), no PII, cached 5min-1h depending on window. This fully informs the agent about behavior beyond the 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 a single focused paragraph (~80 words) with front-loaded purpose, followed by bullet-like use cases, then data source and caching info. Every sentence adds value, 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?

Given no output schema, the description mentions 'top tools, top packs, total call volume' and 'just (pack, tool, count)'. This provides enough structure for an agent to interpret the response. Caching and window specifics are covered. Minor gap: exact format of output not specified, but sufficient for a simple 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% with enum descriptions. The description adds meaning: shorter windows surface what's hot right now, longer windows show steady-state demand. This helps the agent choose appropriate window 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 the tool returns 'top tools, top packs, and total call volume' with specific time windows. The verb 'returns' and resource (trending data) are explicit. It distinguishes from siblings (e.g., query, ask_pipeworx) by focusing on aggregate agent usage rather than direct Q&A.

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 specific use cases are listed (discovering hot data sources, confirming canonical tool choice, aligning use case with agent needs). Window semantics are explained (short vs long windows). However, no explicit 'when not to use' or alternative tool comparison is provided.

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