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

Annotations already declare readOnlyHint=true. The description adds useful behavioral context: 'Keyless-cacheable' indicates caching behavior, and 'History accrues from the day the feature shipped' clarifies data availability. This goes beyond the annotation without contradicting it, though it omits details like rate limits or consequences of no data.

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 extremely concise: three short sentences with no wasted words. The title is front-loaded, and the subsequent sentences efficiently convey the core concept and key behavioral traits.

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?

For a tool with 5 parameters and no output schema, the description covers the core concept (daily time series per facet) and adds caching and data start date. However, it lacks details on return format, how multiple keys combine (logical OR vs AND), or behavior for dates with no data. Given the complexity, there are clear gaps.

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 coverage is 100%, so the baseline is 3. The description does not add explicit parameter-level meaning beyond the schema's own descriptions. However, the high-level context (e.g., 'facet dimension' aligns with the dimension parameter) provides some supporting semantics, but no additional depth.

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 identifies the tool as providing a daily time series over a participant facet dimension, mentioning adoption curves and QoQ trends. It distinguishes from siblings like get_participant_stats and get_participant_history by specifying the time-series nature per facet, but doesn't explicitly compare or contrast with similar sibling tools.

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?

No explicit guidance on when to use this tool versus alternatives. The description implies it's for single-facet daily history, but it does not state exclusions or recommend other tools for different use cases (e.g., get_participant_history for per-participant history).

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