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

Annotations already declare a safe read-only, idempotent operation, but the description adds substantial context beyond those hints: it explains the sample sources, total-only privacy, the share formula, how DMARC and SPF are treated, and the largest-remainder rounding rule. This is rich behavioral disclosure for a no-parameter report.

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 dense but front-loaded with the report's purpose, then follows with necessary caveats about scope and computation. Every sentence provides relevant context, though some calculation details are borderline for a no-parameter read 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 output schema, the description must carry the burden of explaining return values and methodology. It does so thoroughly: totals only, no domains listed, share formula, DMARC vs SPF handling, and rounding. Nothing essential for correct interpretation is 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?

There are zero input parameters, so the description has no parameter semantics to clarify. The baseline for a 0-parameter tool is 4, and the schema correctly reflects that no input is required.

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 the monthly Brazil email security report, covering DMARC rejection and SPF endings for government, banks, and listed companies. It clearly distinguishes this public report from the sibling domain/account management tools by naming the exact dataset and scope.

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 explains when the report applies (monthly, public DNS, free, no account) and implies use for aggregate research rather than domain-specific checks. It does not explicitly name alternative tools such as commsharbor_email_security_check, but the context and constraints are clear.

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