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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the tool's output type ('plain-language verdict'), specific checks performed ('Catches the common traps...'), and a critical limitation ('DKIM is probed at common selectors only, so a miss is not proof DKIM is absent'). This is exemplary transparency about edge cases and potential false negatives.

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 three sentences, each packing important information: purpose, use cases, and limitations. It's front-loaded with the core purpose, has no fluff, and every sentence earns its place. The structure is ideal for quick agent comprehension.

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 tool with no output schema and no annotations, the description covers purpose, when to use, what it checks (SPF, DKIM, DMARC), common pitfalls, and caveats. It gives enough detail for an agent to decide whether to invoke it and interpret the result. The only minor absence is return format details, but 'plain-language verdict' is sufficient given the context.

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 100%, so the schema already documents both parameters. The description adds value by explaining the behavioral context: for 'selector', it clarifies that omitting probes common selectors and that a miss is not proof of absence. It enriches the meaning of the parameters without duplicating schema text.

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 starts with a specific verb ('Check') and resource ('a domain's live email authentication — SPF, DKIM and DMARC'), and clearly distinguishes it from sibling tools like check_security_headers or dns_lookup. It also specifies the output ('plain-language verdict') and scope (whether it is actually enforced), making the tool's purpose unambiguous.

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 explicitly states when to use it ('Use for questions about mail being spoofed, landing in spam, or failing delivery, and to audit a domain's anti-spoofing posture'), providing clear context. It doesn't explicitly name when-not-to-use or alternatives, but the sibling tools are clearly distinct, so the usage guidance is strong.

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