generate_dmarc_record

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

Annotations indicate readOnlyHint and idempotentHint, and the description adds valuable behavioral context: the generated record always includes np=reject regardless of p=, it is re-validated before return, and human approval is required. These details go well beyond the annotations by explaining internal validation logic and output guarantees.

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 compact (four sentences) and front-loaded with the primary purpose. Every sentence delivers critical information: what it does, key parameters, the np=reject behavior, re-validation, and human approval requirement. No wasted words.

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 generation tool with no output schema, the description fully covers what the output looks like (a DMARC record), important constraints (np=reject), validation behavior (re-validated), and usage steps (present verbatim, human approval). It gives an agent everything needed to invoke the tool correctly.

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 coverage is 100%, so baseline is 3. The description adds parameter-related clarity by noting that the `policy` parameter does not influence np=reject ('independently of the p= you choose'), which is not obvious from the schema. However, most parameter semantics are already well documented in the schema descriptions.

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 clearly states the tool's function: 'Build a DMARC record from scratch for a domain that has none, using a validating engine.' It distinguishes itself from siblings by emphasizing 'from scratch' and 'never compose one yourself,' differentiating from validate_dmarc_record and build_dmarc_upgrade.

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 explicitly states when to use: 'for a domain that has none,' and when not to: 'never compose one yourself.' It also provides a clear constraint: 'Present it verbatim; a human must approve before publishing.' This gives strong contextual guidance on when and how to use the tool.

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