Bucket event counts by hour or custom intervals to reveal capture gaps; empty buckets mean no events, often because capture was off.
Hourly (or custom) event-count buckets so capture gaps are honest. Empty buckets mean no events that hour — often capture was off. start required (epoch or YYYY-MM-DD); end defaults to now.
| Name | Required | Description | Default |
|---|---|---|---|
| end | No | ||
| start | Yes | ||
| bucket_hours | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v2.1.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does reasonably well: it discloses bucket granularity, that empty buckets are legitimate data points indicating gaps, and the defaulting behavior of end. It omits auth requirements, ordering, and rate limits, but the output schema covers the return shape.
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?
Three short, front-loaded sentences with no filler; the core semantics and required-parameter note come first. The phrasing 'so capture gaps are honest' is slightly slack but not wasteful.
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?
An output schema exists, so return values need not be restated, and the description adds useful interpretation of empty buckets. However, for a tool with no annotations, no sibling differentiation, and one unexplained parameter, the definition is only minimally sufficient for correct selection and invocation.
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 0%, so the description must compensate. It documents start's accepted formats (epoch or YYYY-MM-DD), its required status, and that end defaults to now. bucket_hours is only hinted at via '(or custom)' and never explained, leaving one of three parameters effectively undocumented.
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 states a concrete output: hourly (or custom) event-count buckets for spotting capture gaps. An agent can tell this is a coverage/aggregation tool rather than a raw event search. It stops short of naming how it differs from siblings like search_events_tool or app_time_summary_tool, which also deal with activity over time.
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?
It explains how to interpret results (empty bucket = no events that hour, often capture off), but never says when to reach for this tool instead of search_events_tool, list_sessions_tool, or app_time_summary_tool. No prerequisites or exclusions are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.