x402 Domain Lookup & DNS Email Auth

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

With no annotations, the description carries the full burden and does disclose two non-obvious traits: it is a paid operation ('$0.003 USDC per call via x402') and it returns per-check status, issues, recommendations, a 0-100 score and A-F grade. 'Audit'/'check' implies read-only, but it never explicitly confirms no side effects, nor does it mention rate limits, lookup timeouts, or whether failed DNS lookups surface as errors.

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?

Two sentences, both front-loaded: the first defines the audit scope, the second covers output and cost. The dense parenthetical enumerations are informative rather than filler, so every clause earns its place.

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 two-parameter, read-only audit tool with no output schema and no annotations, the description covers scope, return shape, and payment requirement well. What is missing is an explicit statement of read-only safety and any error/edge behavior (e.g., domains with no records), which matters given the absence of annotations.

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% and both parameters are self-documenting, so the schema already does the heavy lifting. The description's '(common or given selectors)' and 'key type and length' add only marginal meaning over the selectors default list already present in the schema, so baseline 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?

States a specific verb (audit) and resource (a domain's email authentication DNS) and then enumerates exactly what is inspected: SPF qualifier/lookups, DMARC policy fields, DKIM selectors, MX, BIMI/MTA-STS/TLS-RPT. An agent can tell this apart from a generic 'health' sibling purely from the description, since the enumerated DNS records make the scope unmistakable.

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 domain-audit framing, but the description never states when to reach for this versus alternatives (e.g., the 'health' sibling) or any prerequisites such as needing a resolvable, owned domain. No explicit when-to-use or when-not-to-use guidance is provided.

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 supplied, the description carries the full behavioral burden and does so thoroughly. It discloses returned data categories, absence of registrant personal data, RDAP availability limitations, charging rules, and error behaviors including NXDOMAIN, upstream failure, and bad input.

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 front-loaded with the core purpose and packs dense but relevant operational information into one paragraph. It is longer than typical, but most details earn their place given the absence of annotations and an output schema.

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 annotations and no output schema, the description is highly complete. It explains what data comes back, which TLDs may lack RDAP data, how errors are treated, and how charging works, leaving little an agent would need to infer before calling it.

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% and the single domain parameter is already documented in the schema with examples and normalization notes. The description adds no further parameter meaning beyond what the schema provides, so 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 states a specific resource and action: domain lookup returning DNS records and RDAP registration data. It enumerates record types and registration fields clearly. It does not distinguish this tool from the sibling domain_auth_check or domain_lookup_bulk, so it falls short of a 5.

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 never says when to use this tool instead of domain_auth_check or domain_lookup_bulk. It provides useful operational details such as TLD limitations and charging conditions, but no explicit selection guidance or exclusions.

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 provided, the description carries the full burden and does well: it discloses deduplication, inline per-domain error handling, the exact price ($0.01 USDC via x402) and the condition for charging (only if at least one domain succeeded). It doesn't cover authentication requirements beyond payment or rate limits, which are minor gaps given the tool's scope.

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 tight sentences, front-loaded with the core purpose and scope, then error behavior, then pricing. Every sentence adds distinct value with no fluff.

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?

The tool has no output schema and no annotations, so the description must carry significant weight. It adequately covers what is returned (same as domain_lookup), error handling, pricing, and limits, but it doesn't describe the return format in more detail beyond the sibling reference or explain payment timing—both are relatively minor given the tool's complexity.

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?

The input schema already documents the single parameter with 100% coverage (1-10 domains, min/max). The description adds meaningful semantics beyond the schema by noting that domains are deduplicated, which affects how the array is processed and is not captured in the schema.

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 states a specific verb (bulk domain lookup) and resource (DNS + RDAP registration report) and explicitly distinguishes it from the sibling domain_lookup by being for up to 10 domains in one call. An agent can immediately tell this is the batch version of domain_lookup.

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 gives a clear context for use: when you need the same report for multiple domains (up to 10) in one call, and it references the single-domain alternative domain_lookup. However, it does not explicitly state when not to use this tool (e.g., for a single domain) or list exclusions, so it falls short of the top score.

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 discloses the return contents (service status, price, network) and that the call is free, which is useful, but says nothing about auth requirements, rate limits, or whether failures return errors versus degraded status.

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?

Two short sentences, zero waste, with the purpose ('Free health check') front-loaded ahead of the return-value summary. Adequately sized for a trivial endpoint.

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 zero-parameter tool with no output schema, the description does sketch the return payload, but terms like 'price' and 'network' are undefined and there is no indication of response shape or failure behavior. Just enough to call it, not enough to interpret the result.

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?

The tool takes zero parameters, so per the rubric the baseline is 4. There is nothing parameter-related the description could add.

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 clarifies that 'health' is a free health check that returns service status, price and network, which is more than the bare name conveys. However it never distinguishes this from the sibling domain_auth_check, and 'health check' remains somewhat vague about which service is being checked.

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 only usage signal is the word 'Free', implying it can be called without cost or credentials. There is no statement of when to use this versus domain_auth_check, no prerequisites, and no exclusions.

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