list_events

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

Annotations already declare readOnly and idempotent hints; the description adds substantial beyond-schema detail: start/end range semantics, ascending sort order, how unknown types pass through, and the available:false semantics that distinguish an untouched dataset from an empty one. These are exactly the edge behaviors an agent needs to reason about correctly.

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 compact, information-dense, and front-loaded with the tool's core purpose before moving into filters and edge cases. Every sentence contributes unique, non-redundant information.

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?

Despite having no output schema, the description covers source, filter behavior, ordering, overlap semantics, unknown types, and the absence of a meaningful available:false result. This is sufficient for an agent to confidently select and invoke the tool.

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 schema already documents all four parameters with 100% coverage, so the baseline is 3. The description adds meaningful extra context by explaining that range filters allow overlap matching and by reinforcing that the type parameter is open to new app-defined types.

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 specific verb and resource: it lists logged context events from health-events.json, enumerates the event types, and covers future types. This makes the tool clearly distinguishable from the metric, workout, and sleep siblings without opening the schema.

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 gives clear context for when to use it — whenever a list of context events is needed — and describes the optional filters. It does not explicitly call out sibling alternatives or exclusion conditions, but the context signals and type enumeration make the target use case obvious.

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