UK Data: Email and domain checks

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

With no annotations, the description bears the full behavioural burden. It usefully discloses the transport (DNS over HTTPS) and the cost (1 credit), which are genuine additions. However, it does not say what happens for a non-existent domain, whether missing record types cause an error or are omitted, or whether SPF/DMARC are parsed from TXT records — meaningful gaps for a network lookup tool.

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?

One front-loaded sentence stating the record types and mechanism, plus a parenthetical cost note. There is no redundant or filler wording, and the most decision-relevant information comes first.

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 one-parameter read-only lookup this is close to sufficient, but with no output schema the agent gets no hint about the return shape — whether records are grouped by type, raw strings, or absent when not configured. That omission matters because SPF and DMARC results differ structurally from A/MX records.

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 the single 'domain' parameter is documented structurally, and the description's phrase 'for a domain' adds no syntax or format detail (e.g., no subdomain, trailing-dot or IDN guidance). With one parameter and full schema coverage, the baseline of 3 is appropriate.

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 names a concrete resource (specific DNS record types — A, AAAA, MX, NS, SPF, DMARC) and the lookup mechanism (DNS over HTTPS) for a domain. This clearly separates it from nearby siblings like ssl_check, rdap_lookup and ip_lookup, which examine different artefacts. It lacks an explicit verb such as 'look up' or 'retrieve', but the intent is 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?

There is no when-to-use guidance and no mention of alternatives, despite adjacent tools (ssl_check, rdap_lookup, ip_lookup, email_check) that an agent could plausibly confuse with this one. The only contextual cue is the credit cost, which is budgeting information rather than selection guidance.

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

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

With no annotations, the description carries the full behavioral burden. It does disclose two genuinely useful and non-obvious facts: no email is actually sent (so the agent knows this is passive) and the call costs 1 credit. It says nothing about latency/DNS dependence, caching, or whether results are authoritative.

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?

A single front-loaded sentence with the tool's distinctive checks first, the critical scope caveat second, and cost last. No filler words and nothing an agent must skip over.

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 one-parameter, annotation-free, output-schema-free tool this is close to sufficient: the checks listed implicitly describe what the answer will report. It would be complete with one clause on the response shape (e.g. per-check booleans plus MX hosts), since no output schema exists to fall back on.

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 the baseline is 3, and the schema's own text ('string, required') is thin. The description only adds that the value is 'an email address', which the schema name already implies; it gives no format examples or normalization behavior (e.g. case folding, trimming).

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?

Names a specific resource (an email address) and enumerates the exact checks performed: syntax, MX, disposable, role and free-provider. The parenthetical 'no message is sent' removes ambiguity with any send-email tool, and the resource makes it trivially distinguishable from validators like iban_validate or domain_check. It stops short of a 5 only because no sibling is ever named explicitly.

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 verb 'check' on an email address, which an agent will read as pre-validation before storing or contacting an address. There is no explicit when-to-use, no when-not-to-use, and no named alternative among the many validator siblings (iban_validate, domain_check, ip_lookup). Adequate but leaves routing to inference.

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