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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered; the description then adds non-obvious behavioral caveats: 'days' includes today as an incomplete day, limit is capped at 500, and summing dimension rows does NOT yield totals because of limit and thresholding. These gotchas are exactly what the annotations cannot express. It stops short of describing the response shape, though an output schema exists.

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?

Dense, telegraphic and front-loaded — scope first, then metrics/dimensions, then date semantics, then limit/filter/order/workspace. Almost every clause carries information, though the run-on '...' style and mixed German/English phrasing make it slightly harder to scan than a structured list would be.

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 10-parameter tool with no schema documentation and no annotations covering behavior, the description supplies date semantics, limit ceiling, totals trap, filter grammar, ordering, and workspace scoping. Combined with an existing output schema (so return values need not be explained), an agent has enough to call this 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 0%, so the description carries the full burden, and it largely does: days, start_date/end_date override semantics, limit max, dimension_filter dict shape with all match_type values, order_by/order_desc, and workspace slug are all explained. What is missing is the closed set of legal metric and dimension names (only examples plus '...'), which matters most for an agent building a query against a 0%-coverage schema.

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?

States a specific verb+resource: a custom GA4 report run against the workspace's GA4 property, with example metrics and dimensions that make the output shape concrete. It does not, however, distinguish itself from the many more specific GA4 reporting siblings (ga4_top_pages, ga4_traffic_sources, ga4_conversions, ga4_realtime_users), so an agent still has to infer when the generic report is preferable.

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 rich operational guidance (days vs. start_date/end_date, limit cap, totals via dimensions=[], filter syntax), but it is all intra-parameter usage rather than tool selection. No sentence says when to reach for ga4_report instead of ga4_top_pages or ga4_conversions, which is the main ambiguity given the sibling set.

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