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

Annotations already declare readOnly=true and destructive=false, so the safety profile is covered. The description adds real behavioral context the annotations do not: the result is roughly 500 entries and 130 KB, which warns the agent about payload size and motivates the filtering parameters. It also describes the shape of each entry (category, description, metric type), though the output schema already carries return-value detail.

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?

Three sentences, front-loaded with purpose and the link to ga4_report, followed by the response shape and the size warning. The size figure may look like detail but it directly justifies the closing advisory, so every clause earns its place.

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?

An output schema exists, so return values need no prose exposition, and annotations cover safety. What remains for the description to carry is purpose, payload size, and how to filter, all of which are present, making the definition sufficient for an agent to call this correctly on the first attempt.

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 the baseline is 3. The description adds meaning beyond the schema by illustrating what custom fields look like ('customEvent:plan', 'customUser:tier') and why one would filter to them, which makes the custom_only flag concrete rather than abstract.

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 and resource ('The dimensions and metrics a GA4 property can report') and immediately ties it to the consumer tool ('for ga4_report'). It goes beyond the title by specifying that both standard and property-custom fields are returned, along with API names, categories, descriptions, and metric types, so an agent can distinguish it from siblings like list_ga4_properties or ga4_report without opening the 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 an explicit conditional on the parameters ('pass `search` or `custom_only` unless you need all of it') and signals that this is a discovery step feeding ga4_report. What is missing is any comparison against sibling tools (e.g., when to use this versus list_ga4_properties), so the routing guidance is contextual rather than complete.

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