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

Annotations already establish readOnly, idempotent, and non-destructive behavior. The description adds useful context beyond that: it identifies the endpoints, the rollup nature of the org view, pagination for resolutions, and the available filters. This is meaningful behavioral disclosure for a read tool, though it stops short of describing output shape or edge cases.

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 compact and well-organized, front-loading the main purpose and then enumerating the two views with their key modifiers. The trailing 'Read tier.' fragment is slightly redundant given the readOnly annotation, but it is minor and does not impair clarity.

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 read-only analytics tool with no output schema, the description covers the two views, pagination, and filtering options, which is enough for an agent to call it correctly. It does not describe the response payloads or explain the 'pattern-detected' semantics, but the input schema and annotations fill most gaps.

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 coverage is 100%, and each parameter already has a clear description (including 'resolutions only' scoping and the default/max limit). The description reinforces which filters belong to the resolutions view but does not add substantial meaning beyond the schema, so the baseline of 3 applies.

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 states a specific verb and resource: 'Read organization-wide analytics', then distinguishes the two surfaces (org rollup vs resolutions history). Including endpoint mappings and the explicit 'Read tier' label makes the tool's purpose unmistakable and separates it from the many list/get siblings.

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 makes the internal view selection explicit ('view org' vs 'view resolutions') and notes resolution-specific filters, which implies when each branch is appropriate. However, it does not explicitly say when to prefer this tool over sibling analytics/read tools such as tascan_list_issues or tascan_get_scan_history, so usage guidance is implied rather than stated.

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