RDAP API

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

With no annotations to convey read-only behavior, the description carries the full burden. 'Look up' implies a read operation and 'normalized RDAP data' hints at output transformation, but the description does not disclose error behavior, whether data is fetched live, or how the result is structured beyond listing a few fields.

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 focused sentence that front-loads the core action and resource, then lists returned fields without repetition or filler. Every part contributes useful information.

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 single-parameter lookup tool with full schema coverage and no output schema, the description provides adequate context by specifying the source (RDAP), the normalization, and the key returned fields. It does not explain edge cases such as invalid ASNs or formatting, but the simplicity of the tool makes the definition reasonably 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?

The input schema already fully documents the single 'asn' parameter with an example format and the accepted 'AS' prefix. The description adds no additional parameter-level meaning beyond restating that the lookup is for an autonomous system number, so the baseline of 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 identifies the tool as a lookup operation for autonomous system numbers, names the specific data source (normalized RDAP data), and enumerates the returned fields (holder, country, status, registration dates). This separates it from sibling lookup tools like ip-lookup or domain-lookup by resource type.

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 implies that this tool is for ASN lookups, which is enough to select it over the domain, IP, entity, or nameserver lookup siblings. However, it does not explicitly state when to prefer this tool over alternatives or mention any exclusions or fallback conditions.

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 empty annotations, the description carries the transparency burden. It discloses useful operational context: pooled/batch behavior, plan requirement, and per-domain quota consumption. However, it stays silent on per-domain failure behavior, result aggregation, authentication, and error handling, leaving the behavioral picture incomplete.

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 with no filler: the first names the operation and scope, the second adds the non-obvious constraints about plan and quota. The content is front-loaded and easy to parse.

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 3-parameter tool with fully documented schema, this is broadly complete: it identifies the data source, normalization, batch context, and quota implications. The remaining gaps are non-blocking, such as explicit single-vs-bulk routing and error behavior, and no output schema is expected.

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 covers all three parameters at 100%, so the baseline is 3. The description adds only the quota-per-domain consequence for the domains parameter and does not meaningfully enrich the whois or follow semantics, which the schema already documents well.

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 opens with a concrete verb and resource ('Look up normalized RDAP registration data') and immediately states the batch scope ('several domain names in one pooled call'), which distinguishes it from the singular domain-lookup sibling. The tool's role is 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?

The 'several domain names in one pooled call' phrasing gives a clear trigger for using this tool, and the Pro/Business plan plus quota statement provides an important decision constraint. It does not explicitly say to use domain-lookup for a single domain or list exclusion cases, so it stops short of full alternative routing.

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 burden for behavioral disclosure. It indicates a read operation ('Look up') and describes the output fields (registrar, status, dates, nameservers, contacts). It does not mention the WHOIS fallback, error behavior, rate limits, or response format, which would provide richer transparency, but the core read-only nature is clear.

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 well-structured sentence, front-loaded with the action ('Look up') and the resource ('normalized RDAP registration data'). It covers the key output categories without unnecessary words or repetition.

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?

Given it has no output schema, the description lists the main data categories returned, but omits the response structure and error scenarios. The parameter schema compensates for configuration details. The tool is simple enough that this is adequate, but the lack of any usage or fallback context in the main description keeps it at a minimum-viable level.

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%, so the parameters are well documented. The main description adds no additional parameter meaning, but the schema already explains domain, whois, and follow thoroughly, including defaults and behavioral consequences. The baseline of 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 uses a specific verb and resource: 'Look up normalized RDAP registration data ... for a domain name.' It clearly identifies the tool's purpose and distinguishes it from IP, ASN, and entity lookups in the sibling list. However, it does not explicitly differentiate itself from bulk-domain-lookup, 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 gives no guidance on when to use this tool versus alternatives. It does not mention bulk-domain-lookup, tlds, or other siblings, nor does it state any exclusions or prerequisites. The whois and follow parameter descriptions imply some configuration choices, but tool selection guidance is entirely absent.

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 present, the description carries the full behavioral burden. It discloses that data is 'normalized RDAP data', that only certain RIR handles resolve, and that unsupported use cases (domain registrar/registrant) should go elsewhere. This is solid transparency for a simple read-only lookup, though it does not detail error behavior or response shape.

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 with no fluff. The action and examples lead, followed by scope constraints and an explicit alternative. Every sentence contributes useful selection or invocation information.

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 single-parameter lookup tool, this is nearly complete: it explains the input format, which registries are supported, and which sibling tool to use for domains. The only mild gap is that 'normalized RDAP data' is not expanded into concrete return details, but for this low-complexity tool the description is sufficient for correct selection and invocation.

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 the schema already explains the 'handle' parameter with examples. The description adds the RIR scope and the 'organization or contact identifier' context, but these are largely restatements of what the schema plus tool purpose imply. It does not materially expand parameter semantics beyond 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 action and resource: 'Look up normalized RDAP data for an RIR entity handle.' It gives concrete examples ('GOGL', 'ORG-RIEN1-RIPE') and explicitly distinguishes itself from domain-lookup, so an agent can immediately identify what this tool does and what it does not do.

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 explicitly states when this tool applies: only ARIN, RIPE, APNIC, LACNIC, and AFRINIC entity handles resolve. It also names the alternative for domain registrar/registrant lookups ('comes from domain-lookup instead'), giving clear routing guidance without requiring the agent to infer from sibling names.

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 empty annotations, the description carries the full burden. 'Look up' signals a read-only retrieval and 'normalized' discloses a transformation, while the parenthetical names the output fields. It does not cover error cases or rate limits, but for a simple lookup tool this is not a major gap.

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 sentence with no wasted words; the action, output data, and input form are all front-loaded and clearly structured.

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 lookup tool with no output schema, the description is sufficiently complete: it names the input form and enumerates the return fields. It omits failure behavior and source details, but those are secondary for invoking the tool.

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%, establishing a baseline of 3. The description adds meaning by stating the ip parameter accepts 'an IP address or CIDR block', which the schema's ip description ('IPv4 or IPv6 address') does not explicitly convey.

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 ('Look up') and resource ('normalized RDAP allocation data') with the exact scope ('network range, holder, country, status'). It is clearly differentiated from sibling tools by the explicit IP/CIDR target, unlike domain or ASN lookups.

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 phrase 'for an IP address or CIDR block' provides clear context for when to use the tool. It does not explicitly name alternatives or exclusions, but the sibling tool names make the domain-of-use apparent.

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 present, the description carries the burden of behavioral disclosure. It does convey that the tool returns 'normalized RDAP data' and lists included fields, which gives some insight into output content. However, it does not mention error conditions, output format, DNS resolution behavior, or any limitations, so transparency is only partial.

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, tightly written sentence that front-loads the action and resource, then adds useful detail about the returned data. Every phrase earns its place with no filler or repetition.

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 simple one-parameter lookup tool, the description covers the core invocation need: what to pass and what kind of data to expect. However, there is no output schema, so the description should more fully explain the return shape or format, and it also lacks any guidance about when this tool is preferable to related lookups. These gaps keep it from being fully 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%, so the single 'host' parameter is already well-documented in the schema. The description adds minimal semantic value by reiterating that it applies to a nameserver hostname, but this is largely redundant with the parameter description. Baseline 3 is appropriate because the schema already handles parameter semantics.

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 uses a specific verb ('Look up') and a clear resource ('nameserver hostname'), and further clarifies the scope by listing the returned data categories (IP addresses, status, sponsoring registrar). This distinguishes it from sibling tools like domain-lookup or ip-lookup because the target is explicitly a nameserver, not a domain or IP directly.

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 clearly indicates the intended use case: looking up data for a nameserver hostname. It does not explicitly name alternative tools or state when not to use this tool, but the 'hostname' qualifier provides enough contextual guidance for an agent to select it over sibling tools in most cases.

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 to lean on, the description carries the behavioral burden. It discloses that this is a metadata operation, that it will not consume the monthly quota, and what information it returns when describing a specific TLD. It does not detail response format or rate-limit behavior, but for a read-only metadata tool the disclosed traits are meaningful and sufficient.

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 with no filler. The primary action is front-loaded, the detailed return values are briefly summarized, and the quota-exemption note is a valuable standalone behavioral detail. Every sentence 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?

The tool is simple, has zero required parameters, and the schema covers all parameter semantics. The description fills the remaining gap by explaining what the response will contain in both list and describe modes, and it adds operational context via the quota note. Nothing material is missing for an agent to decide when and how to invoke 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?

All three parameters are already fully documented in the input schema, so the baseline is 3. The description adds useful context for the 'tld' parameter by naming the exact fields returned, but it does not add meaning for 'since' or 'server' beyond what the schema already provides.

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 dual function: list all supported TLDs or describe one with specific details like the answering RDAP server, support date, and field fill frequency. This is a specific verb+resource combination that distinguishes it from the sibling lookup tools, which all perform network/data lookups rather than API metadata discovery.

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 strong contextual guidance by labeling the operation as metadata and explicitly noting it never counts against the monthly quota, signaling safe exploratory use. It does not explicitly name alternative tools or provide when-not-to-use conditions, but the framing clearly separates this discovery/metadata tool from the lookup-focused siblings.

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