get_usage_latency

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

With no annotations, the description carries the full behavioral burden, yet it omits the definition of 'the current period' (rolling 24h? billing cycle?), the result shape, and whether latency data is retained or real-time. It does at least disclose the aggregation level and the three percentiles computed.

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?

A single front-loaded sentence with no filler: the resource, the metrics, the breakdown dimension, and the time scope all appear before the period ends.

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 zero-parameter read tool with no output schema this is close to adequate, but the undefined 'current period' is a real ambiguity an agent cannot resolve from anywhere else, and no return structure is hinted at.

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 tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The scope is instead fixed internally ('current period'), which the description does state.

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 names a specific verb-resource pair (get webhook delivery latency) and qualifies it with the exact metrics (p50, p95, p99) and the breakdown dimension (by feed). This distinguishes it reasonably well from volume-oriented siblings like get_usage_by_feed, though it never names an alternative explicitly.

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?

There is no statement of when to use this tool versus get_usage, get_usage_by_feed, get_usage_hourly, or get_webhook_logs, all of which sit in the same neighborhood. The agent must infer the distinction from the metric names alone.

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