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

The description adds caching behavior ('Cached 5min-1h depending on window'), data provenance ('derived from CF analytics-engine, no PII'), and aggregation characteristics ('Self-aggregating signal'). These go beyond the readOnlyHint/idempotentHint annotations, though it does not disclose rate limits or auth requirements (not applicable given read-only nature).

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 four sentences, each with a clear purpose: what it returns, when to use it, data source, and caching. It's front-loaded with the main purpose and contains no redundant phrases.

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 lacking an output schema, the description covers what is returned (top tools, top packs, total call volume, and record shape as pack/tool/count). Combined with comprehensive annotations and the single optional parameter, the description fully equips the agent to invoke and interpret 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?

The window parameter is fully documented in the schema (enum with default and guidance on short vs long windows). The tool description merely restates the window values without adding new meaning, so it doesn't elevate beyond the baseline for 100% schema coverage.

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 first sentence clearly states what it does: 'Returns the top tools, top packs, and total call volume over a recent window.' It distinguishes itself from siblings by focusing on aggregate call trends from other AI agents, which is unique among the listed 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 provides concrete use cases ('Useful for: ...') that indicate when to use the tool, but does not explicitly name alternatives or exclusion criteria. It explains the value for current events, canonical tool selection, and alignment checking, which gives clear context for usage.

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