get_alert_event_stats

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

Annotations provide readOnlyHint=true, indicating a safe read operation. The description adds valuable behavioral context beyond this: it specifies the tool aggregates data into time windows, collects unique entities and metadata, orders results chronologically with most recent first, and returns paginated results (has_next_page, next_cursor). It also mentions permissions requirements ('Query Data Lake'), which isn't covered by annotations. No contradictions with annotations exist.

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 well-structured with clear paragraphs: purpose, parameter context, result ordering, and return format. It's appropriately sized for a complex analytical tool. However, the detailed return format section (8 bullet points) is somewhat lengthy and could be streamlined, as some of this information might be better covered by an output schema (which exists).

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 the tool's analytical complexity, the description is complete: it explains the purpose, behavioral traits (aggregation, ordering, pagination), and permissions. With annotations covering safety (readOnlyHint) and an output schema existing (implied by context signals), the description doesn't need to detail return values extensively. It provides sufficient context for an agent to understand when and how to use this tool effectively.

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 schema already fully documents all parameters (alert_ids, time_window, start_date, end_date). The description adds minimal parameter semantics beyond the schema: it mentions time windows are 'configurable from 1-60 minutes' (implied by time_window) and that results help identify patterns. However, it doesn't provide additional context about parameter interactions or usage examples beyond what's in the schema descriptions.

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's purpose as analyzing patterns across multiple alerts by aggregating event data into time-based groups. It specifies the verb 'analyze' and resource 'alert event stats', distinguishing it from sibling tools like get_alert (single alert) or get_alert_events (raw events). The description provides specific details about what gets aggregated (entities, metadata) and the goal (identify related activities).

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 implies usage context by stating it helps 'identify related activities' and 'identify temporal patterns', suggesting it's for pattern analysis across alerts. However, it doesn't explicitly state when to use this tool versus alternatives like get_alert_events (which might return raw events) or query_data_lake (which might allow more flexible queries). The guidance is clear but lacks explicit sibling differentiation.

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