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check_spf

Read-onlyIdempotent

Validate a domain's SPF record to identify authorized senders, IP addresses, and syntax errors. Reveals which mail servers are whitelisted, helping audit email trust surface.

Instructions

Look up and validate the SPF record for a domain. Lists all IP addresses and third-party senders authorised to send email on behalf of the domain, flags syntax errors, and shows the trust surface (which mail servers are whitelisted). Use when you need to know who is permitted to send email as a domain. Part of the scan_domain audit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesDomain to check (e.g., example.com)
formatNoOutput verbosity. Auto-detected if omitted.
force_refreshNoBypass cache and run a fresh check. Useful after DNS changes.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
scoreYes
passedYes
partialNo
categoryYes
findingsYes
checkStatusNo
Behavior4/5

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

Annotations already establish that this is read-only, idempotent, open-world, and not destructive, so there is no contradiction. The description adds useful non-obvious behavior beyond those annotations, such as flagging syntax errors and enumerating the 'trust surface'. It stops short of describing cache semantics in prose, but the schema already covers force_refresh.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded, with the first sentence giving the action and resource and the following sentences adding only high-value context: what it returns, whether it detects errors, and when to choose it. There is no filler or repetition of schema details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema, clear annotations, and only three parameters, the description fully supports selection and invocation. It covers purpose, result semantics, syntax validation, and workflow context. The expected response format does not need to be in prose because an output schema is present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents domain, format, and force_refresh, including defaults and intended use. The description adds no parameter-specific information beyond the output-level concept of validation, which matches the baseline of 3 for high coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with the specific action and resource: 'Look up and validate the SPF record for a domain.' It then clarifies what the tool provides beyond the name—listing authorized IPs, flagging syntax errors, and showing the trust surface—making it easy to distinguish from siblings like check_mx, check_dmarc, and check_dkim.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a clear usage trigger: 'Use when you need to know who is permitted to send email as a domain.' It also situates the tool within the broader scan_domain audit, providing enough context for selection, though it does not explicitly call out alternatives or when-not-to-use cases.

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

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