ga4_archive_custom_dimension

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

The description discloses key behavioral traits beyond the schema: archive is permanent, the parameter name cannot be reused, and confirm=true is always required. This is valuable context that the schema does not provide. It doesn't mention side effects like whether existing reports break, but the disclosed permanence and irreversibility are significant.

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 two sentences with no wasted words. It front-loads the core action, then packs critical caveats (permanence, no reuse, confirm requirement) into the second sentence. Every sentence 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?

Given the tool's complexity (3 params, 1 required) and the presence of an output schema, the description covers the most important behavioral caveats. It doesn't explain what the response looks like, but the output schema exists. The main gap is not explaining property_id's role, but the tool is still callable with just dimension_id. Overall, it's complete enough for an agent to invoke 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 must compensate. It mentions confirm=true as a requirement, which adds meaning to the confirm parameter. However, it doesn't explain dimension_id or property_id semantics beyond what the schema names imply. The description adds some value but leaves the agent to infer the meaning of the other parameters.

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 states the action ('Archive a custom dimension') and the resource, distinguishing it from sibling tools like ga4_create_custom_dimension and ga4_list_custom_dimensions. It also adds a critical distinction: GA4 has no delete, only archive, which clarifies the tool's unique role.

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?

The description implies when to use this tool (when you need to archive a custom dimension) and explicitly notes that archive is permanent and the parameter name cannot be reused, which serves as a caution. It doesn't explicitly name alternatives or say when not to use it, but the context is clear enough for an agent to select it appropriately.

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