get_alert_statistics

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

Annotations already establish the tool as read-only, idempotent, and non-destructive, so the description's job is lighter. It adds useful behavioral context about grouping and time-window aggregation, but does not disclose return format, whether limits affect aggregation, or how overlapping buckets are handled.

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 with no filler. The core action and grouping dimensions are front-loaded, and every phrase contributes to understanding the tool's behavior.

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?

The description covers the essential aggregation dimensions and relies on the schema for parameter details. However, with no output schema, 'statistical summary' does not fully specify what the response contains, leaving some ambiguity about the exact return shape.

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 description coverage is 100%, so the parameters are already documented (limit, device, group_id, hours_back, bucket_size_hours). The description maps conceptually to bucket_size_hours and hours_back but adds no semantic detail beyond the schema.

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 uses a specific verb ('Aggregate') and resource ('alert counts'), and names the grouping dimensions (severity, device, datasource, time bucket). It distinguishes itself from raw list tools like get_alerts through the aggregation focus, though 'statistical summary' is somewhat vague about what statistics are produced.

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 aggregation wording implies this tool is for summary counts rather than raw alert listings, but it never explicitly says when to choose it over get_alerts or get_alert_details. No alternatives or exclusions are named, leaving the decision to inference.

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