kpi_dau

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

No annotations are provided, so the description carries the full behavioral-disclosure burden. It does not state that this is a read-only operation, does not mention authentication requirements, rate limits, pagination, or what the returned time series looks like.

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 a single front-loaded sentence with no wasted words. It is appropriately concise for a simple metric endpoint, though its brevity contributes to the broader completeness gaps.

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 5-parameter analytics tool with no annotations and no output schema, one sentence is insufficient. It omits return format, time-window semantics, default behavior, and authentication context that an agent would need to call it confidently.

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 about 80%, so the schema largely documents parameters such as apiKey, app_id, length, and restEndpoint. The description adds no parameter meaning beyond the schema, and ending_at lacks a schema description, leaving a minor gap.

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 metric and temporal scope: 'daily active users (DAU) over time.' It clearly identifies the resource, though it does not explicitly differentiate this tool from siblings such as kpi_mau or kpi_new_users.

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?

There is no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. The only usage signal is the metric name itself, which is implicit at best.

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