ga4_active_users

Does 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 prerequisites (Data API enabled on the quota project, Viewer role on the GA4 property) and error behavior (access failures explain the fix). It stops short of stating that this is a read-only operation, rate limits, row caps, or whether results are cached.

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?

Front-loaded with the metric output then prerequisites, with no filler. Minor deductions for the mixed-language fragment 'Lector (Viewer) en la propiedad de GA4' mid-sentence and for cramming the access-failure guidance into the same dense block.

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 four-parameter, no-output-schema, no-annotation tool, the description covers what is returned (DAU/WAU/MAU and stickiness, optionally per dimension), the access prerequisites, and the failure remedy. An agent could invoke it correctly from this plus the schema; only output shape details are inferred.

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 all four parameters are already documented, including the relative date formats and the property defaulting to ga4_list_properties. The description adds only the notion that split_by accepts an extra dimension such as platform, which the schema already implies with the same example. Baseline 3 is appropriate.

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 names a specific verb (compute daily active users) plus the exact metric set (DAU, WAU, MAU, stickiness ratios) and the optional dimension split. That granularity lets an agent distinguish it from the general-purpose siblings like ga4_run_report or ga4_batch_reports without opening a 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 on when this applies (active-user metrics, optionally split by platform or another dimension) and names the recovery path: if it fails for access, use ga4_check_access. What's missing is explicit routing against overlapping report tools (ga4_run_report, ga4_compare_periods) for agents deciding between them.

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