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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so safety is covered. The description adds useful behavioral context by disclosing what the analysis returns (auth results, alignment, delivery path, delays), which is the key trait for interpreting output on a tool with no output 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, front-loaded with the action and inputs, then the return contents, then the usage trigger. No filler or repetition.

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 single-parameter, read-only tool with no output schema, the description covers input format, analysis scope, and a usage trigger. Nothing an agent needs to select and call it correctly 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?

Only one parameter, and the schema already documents it at 100% coverage ('the part above the message body'). The description's 'raw headers of a received email' and 'pastes headers' reinforces format expectations slightly but adds no new syntax or constraints. Baseline 3 applies when the schema does the work.

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?

States a specific verb and resource ('Read the raw headers of a received email') and enumerates what is extracted: SPF, DKIM, DMARC results, alignment, delivery path and delays. This implicitly distinguishes it from domain-configuration siblings like check_spf or check_dkim, since it analyzes a received message rather than a domain's DNS setup, though no sibling is named.

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?

Gives a clear triggering scenario: 'Use when someone pastes headers and asks why a message went to spam or failed authentication.' This tells the agent the input shape and intent. It stops short of naming alternatives (e.g. check_dmarc for domain-level validation) or stating when not to use it.

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