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

The readOnlyHint annotation already conveys the no-mutation behavior, and the description adds context about which preference categories are included. No extra behavioral details (auth, rate limits, return shape) are disclosed, but the annotation reduces the burden for this simple read tool.

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?

A single sentence states the purpose first, then a parenthetical list of the covered preference categories. There is no filler and the structure is easy to scan.

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 two-parameter read-only tool with readOnlyHint and full schema documentation, the description is largely complete. It does not describe the returned output structure, but the category list communicates the core output intent.

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%, which sets the baseline at 3. The description does not directly explain the parameters, but the schema already fully documents user_id and tenant_id, including the tenant_id scoping guidance.

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 identifies the verb-resource pair: 'Get a user's notification preferences' and enumerates the content categories (subscriptions, opt-outs, channel preferences). It does not name or contrast siblings such as get_user_preference_topic, so it stops short of full sibling differentiation.

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 itself implies no when-to-use guidance, but the tenant_id parameter schema carries an explicit usage note ('Omit this to get the user's workspace-level preferences... Only pass it when you need the tenant-scoped overrides'). That directs parameter choice but not tool choice between alternatives.

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