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

Annotations already mark this as read-only, and the description adds valuable behavioral details beyond that: bucketing is auto-chosen from the time window, gaps are zero-filled, and the result is safe to plot directly. This goes well beyond the readOnlyHint and helps an agent trust the output shape without hidden nulls or missing periods.

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 three sentences with no filler. Each sentence adds distinct value: what the series is, how it is structured, and when to use it. The core meaning is front-loaded in the first sentence.

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?

Complemented by an output schema, read-only annotations, and fully documented optional parameters, the description covers what the time series contains, how bucketing works, how missing data is handled, and a clear use case. Nothing essential is missing for an agent to select and invoke this tool correctly.

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 both parameters (embed_types and time_filter) are fully documented in the schema. The description does not need to repeat parameter details, though it adds some conceptual context about interaction types. Baseline 3 is appropriate since the schema carries the parameter explanation burden.

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 returns a time series of active sessions, bucketed by day or week and broken down by interaction type. It specifies the resource ('active sessions'), the action ('time series'), and the structure ('each row breaks the total down'), making it distinct from sibling tools like get_active_sessions_by_embed.

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 explicitly says 'Use this to spot spikes, dips, or trends,' giving an actionable use case. It does not explicitly mention alternatives, but the context is clear enough that an agent can infer when this tool is appropriate versus non-time-series analytics tools.

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