get_usage_by_feed

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

No annotations exist, so the description carries the burden. It does disclose the shape of the result (counts grouped by feed, limited to the current period), but leaves 'current period' undefined, says nothing about whether failed deliveries are counted or what units/totals appear, and gives no auth or rate-limit context.

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?

Two short sentences, zero filler. The core deliverable — counts by feed — is front-loaded, and the use case follows immediately.

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, the description covers what is returned and the scope. The main residual gap is the undefined 'current period', which an agent must guess at given there is no parameter to control it.

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 the baseline is 4. There is nothing for the description to compensate for, and it correctly frames the implicit 'current period' scoping rather than implying a configurable window.

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?

States a specific verb and resource: webhook delivery counts, explicitly broken down by feed and scoped to the current period. The 'broken down by feed' qualifier distinguishes it from aggregate siblings like get_usage and get_usage_hourly, though it never names them.

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 sentence 'Useful for identifying which feeds are driving delivery volume' supplies a use case, which implies when to reach for it. But there is no explicit when-not guidance and no named alternative (get_usage, get_usage_latency, get_usage_hourly) to route against, leaving the choice to inference.

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