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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable context by warning that returned data may not be fresh and must be inspected before comparing activity—information not derivable from the annotations or schema.

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?

Two sentences, no filler, with the core purpose front-loaded and the caveat placed right after. Every word adds value and the structure is easy to parse.

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 this is a no-parameter read-only discovery tool with no output schema, the description covers the essential context: what is returned, what it is not, and a freshness caution. Nothing significant is missing for an agent to invoke it 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?

The tool has zero parameters and the schema coverage is effectively 100%, so there is no parameter documentation burden. Per the baseline for zero-parameter tools, the description is adequate without adding parameter-level detail.

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 uses a specific verb and resource: 'Discover configured Live views, their time windows and rule versions.' It clearly identifies the tool's output scope and distinguishes it from 'customer Lists,' which is especially useful given the sibling list_lists tool.

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 explicitly states what this tool is not ('These are not customer Lists') and gives actionable guidance for a common use case ('inspect returned freshness before comparing activity'). This exclusion plus behavioral caution tells an agent when to prefer this over list-oriented siblings.

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