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

With no annotations provided, the description carries the full burden and exceeds it: it discloses the two-array structure that must never be merged, enumerates all alert/finding types, specifies ordering priority, describes returned contents (evidence numbers, money at risk, weekly summary), and gives presentation rules ('suggest the action, never promise results', label AI summaries). This is rich, actionable behavioral disclosure.

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 long but every sentence earns its place: the critical two-array constraint is front-loaded, followed by item taxonomies, ordering rule, contents, account_id behavior, and response language guidance. Density is justified by the complexity of the output contract.

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 no output schema and 5 parameters, the description fully covers output shape, item semantics, ordering, included fields, and how to phrase the response. The un-documented parameters are simple enums/defaults, so nothing an agent needs to invoke the tool correctly is materially missing.

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 low (20%, only account_id documented), and the description adds no new parameter meaning beyond repeating the account_id omission guidance already in the schema. However, the remaining parameters (limit, status, platform, include_dismissed) are largely self-explanatory through their types, enums, and defaults, so the gap is a clear but not severe shortfall.

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+resource ('Verified recommendations AND alerts computed by ADSAP's daily/weekly checks') and immediately distinguishes the two output arrays (alerts vs findings) with concrete item types. This clearly separates it from the many sibling get_* tools, which focus on raw metrics, health, or assets.

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 gives clear context on when the data is relevant (daily/weekly checks from the client's own data) and explicit handling guidance ('When both are present lead with the alerts', 'Omit account_id for a whole-workspace view'). It does not explicitly name alternatives or state when-not-to-use, but the unique recommendations/alerts scope makes the intended use clear.

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