dmarc_generateGenerate a DMARC DNS record for a domain. Returns the record name, value, and type ready to be added to DNS.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | The email address to receive DMARC aggregate reports, e.g. dmarc@example.com | ||
| domain_name | Yes | The domain to generate a DMARC record for, e.g. example.com | |
| dmarc_policy | Yes | The DMARC policy: none (monitor only), quarantine (mark as spam), or reject (block entirely) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds value beyond annotations by disclosing that the tool 'Returns the record name, value, and type ready to be added to DNS', clarifying that it only generates the record and does not apply it. This complements the idempotentHint and the non-destructive nature, enhancing transparency.
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 a single, concise sentence that front-loads the primary action and then specifies the return value. No wasted words; every element serves a purpose.
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 straightforward generator with full schema and annotations, the description provides enough context: what it does and what it returns. It omits details like the exact DNS record format, but the schema and the simplicity of the tool make it sufficiently complete.
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% with each parameter well-explained (domain, email, policy). The tool description does not add further parameter details, but the schema already handles the heavy lifting, so the baseline 3 applies.
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 'Generate a DMARC DNS record for a domain' with a specific verb and resource. It is easily distinguished from sibling tools like dmarc_check (which checks existing records) and spf_generate (which generates SPF records).
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?
Usage is implied by the tool's name and description: use when you need to create a DMARC record. However, there is no explicit guidance on when to use this instead of alternatives like dmarc_check, or any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a specific purpose, but dns_lookup overlaps with cname/mx/ptr/txt lookups since it returns all record types. The 'check' tools validate records while 'lookup' tools merely retrieve them, which helps differentiate, but an agent could still confuse e.g., txt_lookup with dkim_check.
Naming follows a noun_action pattern (e.g., bimi_check, mx_lookup) but uses inconsistent actions: check, lookup, finder, and generate. 'imap_finder' and 'smtp_finder' break the noun_verb pattern, and there is no uniform verb choice.
With 16 tools, the count is at the upper edge of reasonable for an email deliverability domain. The individual DNS checks and server tests are justified, but some consolidation (e.g., a single lookup tool with record type parameter) could reduce redundancy.
Covers critical authentication checks (SPF, DKIM, DMARC, BIMI), blacklist checks, DNS lookups, and SMTP/IMAP connection tests. Missing DKIM generation and deeper reputation tools, but core deliverability verification is well-covered.