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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds real behavior beyond that: every member of the token's company can see and answer every case, replies land in the case thread and also reach followers by email, attachments are web-app only, and agent writes are labeled 'via AI agent'. Much of this is support-case context rather than this specific summary's behavior, keeping it just below a 5.

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?

Front-loaded with the purpose and the two metric definitions, then usage, which is the right order. It is somewhat long and includes tangential material (email delivery of replies, web-app file attachments) that does not help call this particular tool.

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?

With no parameters and no output schema, the description carries the burden and does define the two counts it returns plus visibility scope, which is most of what an agent needs. It never states the concrete response shape (e.g., a two-field count object) or whether counts are scoped by filters, leaving a small gap.

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?

There are no input parameters, so the baseline is 4, but the description goes further and defines the semantics of the values it returns ('waiting_customer' = cases the BoardMark team answered and awaits the company; 'open' = cases not closed) — meaningful interpretation help given no output schema exists.

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 precisely what the tool returns — a company-wide count of cases waiting on the customer versus cases still open — and even defines each metric. It distinguishes itself from get_support_case (read a thread) and from issue tools, so an agent can identify it without opening the schema.

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?

Explicit routing: use support cases when the user wants help from the BoardMark team or reports a bug/sign-in/billing/feature request, and 'never for the user's own project work (that is issues: create_issue, search_issues …)'. Both the when and the when-not are named, along with the alternative tool family.

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