DomainKits

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

Annotations already declare read-only, idempotent, and non-destructive behavior, so the bar for additional transparency is lower. The description adds valuable context: a ~240 million domain database, the market-analysis purpose, and the critical fact that results are already registered. No contradiction with annotations.

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 plus a related-tools line, with the main verb and purpose front-loaded. Every sentence earns its place; there is no fluff or repetition of schema details. The structure is tight and scannable.

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 10-parameter tool with no required fields, an output schema, and strong annotations, this description provides sufficient context to select and understand the tool. It covers data source, purpose, and major limitation. It could mention pagination or return format, but the output schema covers return structure, so this is acceptable.

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 baseline is 3. The description only summarizes the filter categories (keyword, TLD, length, character set) without adding new details beyond what the schema already provides. It does not elaborate on position, status, or sort semantics, but those are well-covered 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 clearly states a specific verb ('Search') and resource ('active gTLD domains'), with concrete filters (keyword, TLD, length, character set). It distinguishes itself from sibling tools by noting results are registered domains and not available for registration, and it mentions related tools (expired, whois, dns).

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 clear context for when to use this tool (market-analysis of keyword distribution and saturation) and explicitly states a key exclusion: results are not available for registration, implying it is not for availability checks. However, it does not explicitly name alternative tools like 'available' or provide when-not-to-use examples beyond the registered-domain caveat.

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?

Annotations already declare readOnly, idempotent, and non-destructive. The description adds clarity that results are live domains owned by others, with an age range of 5-20+ years, and that filters include keyword, TLD, age, length, and sale status. This is useful context beyond the annotation flags.

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 plus a related-tools line pack the essential information with no fluff. The purpose and the critical distinction from expired domains are front-loaded, making it easy to scan.

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 the full param descriptions, output schema, and safety annotations, the description covers the key context: what the tool searches, the nature of results, and related tools. No critical information is missing.

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?

With 100% schema description coverage, the schema already documents all 12 optional parameters, including enums. The description's mention of filter dimensions roughly maps to parameters but doesn't add new semantic details, so it earns the baseline of 3.

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 searches currently registered domains with 5-20+ years of history, with specific filter dimensions (keyword, TLD, age range, length, sale status). It distinguishes from siblings by noting these are live, owned domains rather than expired or unregistered ones, and lists related tools.

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 usage via 'currently registered domains' and 'not free to register,' which contrasts with expired domain search. The 'Related: expired, whois, dns' line points to alternatives, but it doesn't explicitly say when to choose one over another.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds the scope ('single domain') and output focus ('registrability and price') but no further behavioral traits such as rate limits or error handling, so it offers modest value beyond annotations.

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: the first states the action and scope, the second reinforces authority, and the Related line adds cross-reference. No extraneous text.

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?

With a single parameter, a complete schema description, strong annotations, and an output schema present, the description adequately covers what the tool does and when to use it. The related-tools pointer adds contextual completeness.

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 only parameter, 'domain', is fully documented in the schema with format example. The description adds no additional parameter semantics, leaving this at the baseline for high schema coverage.

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 'Confirm a single domain's registrability and price' with a specific verb and resource, and explicitly contrasts with bulk_available, whois, and monitor via the 'Related' line, effectively distinguishing this tool from siblings.

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 notes it is for a single domain, implying bulk_available is for multiple, and lists whois and monitor as related alternatives. This provides clear context for when to use this tool, though it stops short of explicit 'use X instead' 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?

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is known. The description adds no further behavioral details (e.g., rate limits, data freshness, or side effects). It focuses on output content, which is purpose rather than behavior. With strong annotation coverage, a score of 3 is appropriate.

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 consists of two short sentences: the first states the core functionality with a clear list of outputs, and the second names related tools. There is no fluff, and the key information is front-loaded.

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 (one parameter), has an output schema, and the annotations cover safety. The description adequately covers what the tool does and points to related tools. Nothing important is missing for an agent to select and invoke it correctly.

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 schema has 100% coverage for the single parameter 'domain' with a clear description ('Domain name (no protocol or path)'). The description itself does not add parameter-level detail beyond what the schema provides, 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 states the tool returns a domain's backlink profile and lists specific metrics (domain rank, backlinks, referring domains, spam score, link distribution). The verb 'Return' plus the resource ('domain's backlink profile') makes the purpose unmistakable and differentiates it from other SEO tools like whois and safety.

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 mentions 'Related: whois, safety' which hints at related tools, but it does not explicitly state when to use this tool versus alternatives. There is no direct exclusion or condition, so the usage is mostly implied by the tool name and the listed output. This is adequate but not explicitly guided.

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?

Beyond annotations, the description adds valuable behavioral context: it states that the status is point-in-time, that MCP does not infer availability from failures, and that affiliate fields are removed from the upstream response. These details help the agent interpret results correctly and set expectations about response sanitization.

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 paragraph that front-loads the core purpose, then explains status values and behavioral nuances. It is slightly lengthy due to the status definitions, but each sentence serves a purpose and there is no redundancy or 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?

Given the output schema exists, the description does not need to document return format. It explains all domain status meanings, the limits, and key behavioral quirks. It does not mention potential errors or rate limits, but for a batch read-only tool with one parameter, it is largely 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 schema already fully describes the 'domains' parameter (comma-separated, max 50). The description repeats the 50-domain limit but does not add new parameter-level information, such as formatting or validation details. Hence, the description adds minimal semantic value beyond 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?

The description clearly states the tool returns point-in-time availability status for up to 50 domains, with a specific verb ('Return') and resource ('Availability service'). It also defines each possible status value, distinguishing this batch tool from singular alternatives like 'available'.

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 usage for batch queries by specifying 'up to 50 domains' and explaining the status semantics. It does not explicitly name alternatives or exclusion criteria, but the batch scope and threshold provide clear context for when this tool is appropriate.

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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, which cover safety. The description adds value by specifying the exact categories returned (taken, available, listed for sale) and the batch-processing nature, going beyond the annotations without contradicting them.

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 concise and front-loaded: the first sentence delivers the core purpose and outcome, and the second sentence points to related tools. Every word is purposeful, with no redundancy or 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 is simple (one parameter) and has an output schema and rich annotations. The description covers the main behavior and outcome categories. However, the lack of explicit guidance on when to prefer this over related tools and the minor singular/plural wording issue prevent 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?

The schema fully documents the 'keywords' parameter (comma-separated, max 50), so the baseline is 3. The description adds the TLD-checking context but introduces a slight inconsistency by saying 'one keyword' while the schema permits multiple keywords. This does not clarify parameter usage 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 clearly states the action ('Check registration status'), the resource ('one keyword across many TLDs'), and the outcome ('returning which TLDs are taken, available, or listed for sale'). It also distinguishes itself from siblings by emphasizing 'at once' and listing related tools like tld_check and available.

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 bulk usage through 'across many TLDs at once' and references related tools, but it does not explicitly state when to use this tool vs alternatives. There is no direct 'use tld_check for single TLD' guidance, so the usage context is only implied.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe read operation. The description adds a little context about the domain deletion lifecycle, but no additional behavioral details like pagination limits or rate constraints. No contradiction with annotations.

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 main purpose and key filters are front-loaded in the first sentence, and the second sentence lists related tools. Every sentence 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?

The description effectively summarizes the tool's purpose and key filters for a 12-parameter search tool. An output schema exists, so return values need no explanation. It could mention the meaning of 'hold' status or sorting, but the schema covers those fields, and the description gives enough context for correct tool selection.

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 all 12 parameters are documented in the schema. The description recaps the filter dimensions (keyword, TLD, age range, length, character set) but adds little beyond the schema—only a slight connection between 'open for immediate registration' and the 'hold' parameter's 'no_hold' enum.

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 searches for domains that have completed the deletion cycle and are open for immediate registration, which is a specific verb+resource+scope. It mentions related tools but does not explicitly differentiate them from siblings, so it stops 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?

Usage context is implied through the description (search for deleted domains ready for registration), but there is no explicit when-to-use vs alternatives guidance. The 'Related:' line lists sibling tools but does not explain when to choose this tool over them.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds that results include nameservers and hosting-related records, which is useful behavioral context. However, it does not disclose response format or other behaviors beyond what annotations provide, so it adds moderate value.

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 concise, consisting of two sentences. The first sentence states the primary purpose, and the second lists related tools. There is no waste or redundancy, and the information is front-loaded.

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 lookup tool with one parameter, an output schema, and comprehensive annotations, the description is fairly complete. It explains the scope of the lookup (nameservers, hosting records) and mentions related tools. However, it could be more explicit about when to prefer this tool over the related ones, which prevents a perfect score.

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 schema has 100% parameter coverage with 'domain' described as 'Domain name'. The description adds no further meaning beyond this, such as format, examples, or constraints. Since the schema already documents the parameter adequately, 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 clearly states the tool resolves a domain's DNS records, specifying nameservers and hosting-related records as included content. It uses a specific verb ('Resolve') and a resource ('a domain's DNS records'), but it does not explicitly differentiate from sibling tools like whois or ns_reverse, only listing them as related.

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 mentions 'Related: whois, ns_reverse,' which implies these are alternatives but does not provide explicit guidance on when to use dns versus those tools. The usage context is implied by the description's focus on DNS records, but no exclusions or direct comparisons are given.

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?

Annotations already declare read-only and idempotent behavior. The description adds useful context by defining premium domains as short 1-4 letter and high-value single-word names, and by specifying the 24-hour time window. This goes beyond the annotations without contradicting them.

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 concise at two sentences, with the first sentence front-loading the core purpose and scope. The second sentence about related tools is brief but helpful for orientation, though it could be seen as filler.

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 the rich input schema (7 params, 100% coverage), output schema, and comprehensive annotations, the description adequately covers the core purpose and premium domain definition. It does not explain pagination or keyword search, but these are documented in the schema.

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 has 100% coverage with descriptions for all 7 parameters, so the description does not need to explain them. The description only names 'reason' and 'length' filters, which adds marginal meaning beyond the schema but is not necessary.

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 lists registration and status changes for premium .com domains in the past 24 hours, with filtering by reason and length. The specific scope (premium domains, 24h window) and verb 'List' distinguish it from sibling tools like whois and ns_reverse.

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 mentions 'Related: whois, ns_reverse' but provides no explicit guidance on when to use this tool versus those alternatives. The title and description imply a monitoring use case, but there are no clear when-to-use or when-not-to-use instructions.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the agent knows it's a safe read operation. The description adds behavioral context: domains are still held by the current registrant and acquisition windows are time-sensitive, which informs the agent about the dynamic nature of results. No contradictions.

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 plus a related-tools line, all concise and front-loaded. No filler or redundancy.

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 description captures the core purpose, a key behavioral nuance, and related tools. With an output schema present, it doesn't need to explain returns. Minor gap: mentions 'drop date' which is not a direct parameter (covered under status), slightly reducing completeness, but overall sufficient.

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 schema fully documents all 13 parameters with enum descriptions. The description merely lists filter categories (lifecycle status, TLD, age range, drop date, length, character set) without adding detail beyond the schema. 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 the tool searches domains in the deletion cycle (expired, redemption, pending delete), explicitly listing lifecycle statuses. It distinguishes from siblings like 'deleted' by noting these domains are still held by the current registrant, making the purpose 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?

The description provides clear context on when to use this tool: for domains in the deletion cycle with time-sensitive windows. It mentions related tools (monitor, deleted, whois) but does not explicitly state when not to use them, leaving some comparison implicit. This is more than implied usage but lacks explicit alternatives.

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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is known. The description adds the data fields returned but does not provide additional behavioral context such as pagination, rate limits, or error conditions. It neither contradicts annotations nor adds significant behavioral insight beyond them.

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 two concise sentences. The first sentence states the core function clearly, and the second adds a related-tool pointer. No filler or redundancy; every word 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?

Given the presence of a full output schema and annotations, the description is sufficient for a simple lookup tool. It covers the primary return data, mentions a related tool for alternative use cases, and avoids needing to explain return structure. It is complete for its complexity 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 schema fully documents both 'keyword' and 'country', including the country enum and default. The description does not add extra parameter semantics beyond mentioning 'keyword' as the central input, which is already obvious from the schema and tool name.

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 returns search-volume, CPC, and competition data for a keyword, using a specific verb and resource. It also distinguishes itself from the sibling tool keywords_trends by naming it as related, clarifying the scope.

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 hint about related tool keywords_trends, implying an alternative exists, but it does not explicitly state when to use this tool versus the alternative. The usage context is only implied, not clearly defined.

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?

The description adds valuable behavioral context beyond annotations: it discloses that results are 'representative samples, not a complete registry feed, demand measurement, valuation, or investment recommendation.' It also warns that scope=com is not available for prefix, which is a non-obvious constraint. This complements the readOnly/idempotent annotations well.

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 sentences, each earning its place: purpose, type/scope semantics, and caveat. It is well-structured, front-loaded with the main action, and contains no redundant or filler text.

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 the tool's moderate complexity (2 enum params, output schema present), the description fully covers what the tool does, the meaning of each parameter, and important limitations. The output schema handles return format details, so nothing else is needed.

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?

Although schema descriptions cover 100% of parameters, the tool description enriches them significantly. It explains that 'hot' and 'emerging' cover rolling keyword cohorts, while 'prefix' returns prefix activity buckets, and further details the difference between scope=all and scope=com including availability restrictions. This adds real meaning beyond the enum lists.

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 specific verb and resource: 'Return provider-computed keyword registration statistics.' It clearly distinguishes itself from sibling tools by focusing on keyword trends (vs. tld_trends, keyword_data) and explains the three data types (hot, emerging, prefix) with enough specificity to orient the agent.

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 provides clear context for when to use the tool by explaining the meaning of each type and scope option. It doesn't explicitly name alternative tools or exclusion scenarios, but the information given is sufficient for an agent to decide when this tool is appropriate.

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?

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds valuable behavioral context by clarifying that results are live, owned domains and that it filters on marketplace listing data, which is beyond what annotations provide. No contradiction with annotations.

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 concise, two sentences plus a related-tools line, with the action and subject front-loaded. No filler or redundancy.

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 11 parameters and an output schema, the description is sufficiently complete. It captures the core purpose and mentions the key filters. The special TLD-browse mode is visible in the schema, and the output schema covers return structure, so no major gaps.

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 met. The description only summarizes the main filters (keyword, TLD, status, length, character set) without adding new meaning or parameter interactions beyond the schema. It neither compensates nor detracts from 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 clearly states the tool searches currently registered domains carrying marketplace listing data, with specific filters (keyword, TLD, status, length, character set). It distinguishes itself from sibling tools like 'available' or 'deleted' by emphasizing 'currently registered' and 'owned by someone', and references related tools for niche purposes.

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 usage by defining the scope (registered domains with marketplace data), but offers no explicit when-to-use or exclusions. The 'Related: keyword_data, tld_check' hint is a pointer but does not elaborate on when to choose this tool over those alternatives.

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?

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds meaningful behavioral detail by enumerating possible return statuses and the 'when available' price condition, as well as the Sedo-only data source. This goes beyond what the annotations state.

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 compact and front-loaded with the core purpose, followed by return behavior and scope limitation. Each sentence contributes useful information, and the related-tool reference is brief and relevant.

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 the tool's simplicity, the presence of an output schema, and strong annotations, the description covers all necessary context: purpose, return values, data source exclusivity, and related tools. No critical behavioral or usage information is missing.

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 schema fully documents the single 'domain' parameter with an example, so the description does not need to add parameter-level detail. The description's mention of 'domain' adds no new semantic information 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 uses a specific verb ('Check') and resource ('Sedo aftermarket listing price for a domain'), and clearly states what it returns (status and price). It also distinguishes itself from other marketplaces and related tools, making its purpose 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?

The description clearly identifies when to use the tool by limiting scope to Sedo and explicitly excluding other marketplaces. It names related tools but does not provide an explicit when-to-use vs. when-not-to-use comparison beyond the data source boundary.

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?

The description adds valuable behavioral context beyond the minimal annotations: data is encrypted at rest (AES-256-GCM) in a private per-user directory, account/memory requirement, tier maximum for 'set', and backward compatibility for dns/whois parameters. The actions disclose side effects ('delete: remove a monitor'). No contradiction with annotations (readOnlyHint=false aligns with mutating actions; destructiveHint=false is arguable given the delete action, but the description makes the behavior explicit, so no contradiction).

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 well-structured: an introductory sentence, a bulleted list of actions, and a final prerequisite note. It is moderately sized and front-loaded with the core purpose. Some slight redundancy (e.g., WHOIS/DNS/web_fetch appear in both the intro and actions), but it remains readable and every section adds 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?

The description covers the essential context: purpose, actions, prerequisites, security, and limits. An output schema exists, so return-value details are not required. For an 8-parameter tool with no required parameters, the description manages to explain the conceptual model and action-specific usage comprehensively. Minor omissions like error cases or pagination are not critical.

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. The description adds meaning beyond the schema by associating parameters with specific actions (e.g., 'domain (set only)', 'dns (update only)' appear in the schema but the description reinforces this with the action breakdown and adds 'backward compatibility' context. It also clarifies the 'action' parameter defaulting behavior, which is not explicitly stated 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 clearly states the tool's purpose: 'Manage cross-platform domain monitoring tasks that track changes in WHOIS, DNS, and host-supplied page content.' The verb 'Manage' plus the resource 'domain monitoring tasks' is specific. It also lists four actions (get, set, update, delete), further clarifying its role as a CRUD manager. While it doesn't explicitly compare to sibling tools, the focus on task management distinguishes it from direct lookup tools like whois and dns.

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 action-level usage guidance and a prerequisite ('Requires a registered account with memory enabled'). It also notes tier limits for 'set' and defaults for 'action'. However, it does not explicitly state when to use this tool versus alternatives, nor when not to use it. Sibling tools like whois and dns are not mentioned, so the guidance is implied rather than explicit.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds the 60-day window and browsing mode, which is useful context, but does not disclose other behaviors like pagination or rate limits. Since annotations cover the main safety traits, the description adds moderate value.

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 two sentences, front-loaded with the primary purpose, followed by a filter summary and related tools. Every word earns its place with no redundancy or 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?

Given the rich input schema (13 params, 100% coverage, enums) and the presence of an output schema, the description provides a complete overview of the tool's core functionality and browsing modes. It does not repeat schema details, but covers the essential usage context.

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 baseline is 3. The description mentions filter categories (recency, registration term, length, character set) that map to several parameters, slightly reinforcing the schema, but does not add substantial meaning 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 states a specific action ('Search newly registered domains') with a clear resource and scope (last 60 days, all TLDs or a single gTLD). It distinguishes itself from siblings by focusing on new registrations and offering both keyword and browse modes.

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 provides clear context for when to use the tool (searching newly registered domains by keyword or browsing a gTLD) and mentions related tools, but does not explicitly state when not to use it or contrast with alternatives. The usage is clear enough without explicit 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds that it finds all gTLD domains with filtering, but it does not disclose pagination behavior or other operational details beyond the schema.

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 two concise sentences: a front-loaded purpose statement and a related-tools reference. It contains no fluff and every word contributes value.

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 11 parameters, but the schema documents all of them and an output schema exists. The description captures the core purpose and key filters, making it sufficiently complete for a read-only lookup, though it could mention pagination implications given the 'all' claim.

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% with detailed descriptions for all 11 parameters. The description mentions TLD and keyword filters but adds minimal meaning beyond the schema, 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 clearly states a specific action—'find all gTLD domains hosted on a specific nameserver'—with scope and filters. It distinguishes itself from related tools by explicitly naming whois and dns as alternatives.

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 includes 'Related: whois, dns' which hints at alternative tools but does not explicitly state when to use this vs. those. The context implies this is for reverse NS lookups but lacks clear exclusions or decision 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?

Annotation Contradiction: The description states 'delete: permanently erase all stored user data (GDPR Article 17)', indicating destructive behavior, while annotations declare destructiveHint: false. This is a direct contradiction, forcing a score of 1 despite otherwise valuable transparency about encryption and consent requirements.

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 concise and well-structured: a one-line purpose summary, a brief security note, and a bulleted list of actions. Every sentence serves a clear function, and the action list is front-loaded and easy to scan.

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 description provides rich context: encryption, per-user isolation, action semantics, consent requirements, and GDPR erasure. It also references related tools and the output schema exists. However, the contradiction with annotations on destructiveness undermines reliability, and usage differentiation could be stronger.

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 covers 100% of parameters with descriptions, so baseline is 3. The description adds minimal extra parameter semantics beyond schema, mostly reiterating the memory_enabled prerequisite also noted in the schema. No new behavioral details for individual parameters are provided.

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 manages user preferences and memory settings, then enumerates three specific actions (get, set, delete) with distinct behaviors. It also names related tools (monitor, strategy), which helps distinguish scope.

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 usage context by explaining actions and prerequisites (e.g., memory_enabled must be true, explicit consent for set), but it does not explicitly state when to prefer this tool over siblings like monitor or strategy, nor does it provide exclusion criteria.

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?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds the detail that it returns both registration and renewal pricing, which is useful context beyond the annotations. However, it does not disclose whether pricing is current, cached, or subject to variation, so it only partially complements the annotations.

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 extremely concise at one sentence plus a related note. Every word earns its place, and the key information is front-loaded. It is not overlong, though the 'Related: available' line could be seen as slightly tacked-on rather than integrated.

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 the tool's simplicity (one parameter), the presence of a full output schema, and strong annotations, the description covers the core functionality adequately. It states what is returned and hints at a related tool. It lacks a bit of context about edge cases (e.g., unsupported TLDs), but for a simple pricing query it is 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?

The input schema has 100% description coverage for the sole parameter 'tld', explaining comma-separated multiple TLDs. The description does not add any additional parameter semantics beyond what the schema already 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 clearly states the tool returns 'standard registration and renewal price for a TLD', specifying the resource and action. It is not a tautology and provides a concrete function. However, it does not explicitly distinguish from siblings like 'market_price' or 'tld_trends', so it misses the top score.

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 hint is the vague 'Related: available', which implies a connection to availability checks but does not explain when to use this tool vs alternatives. There is no explicit when-to-use or when-not-to-use guidance, and sibling names like 'market_price' remain unaddressed.

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?

Annotations already declare readOnlyHint and idempotentHint, establishing a safe read operation. The description adds the specific data source (Google Safe Browsing) and the nature of the result (status), which slightly expands beyond annotations, though no further behavioral details are given.

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 two sentences, with the main action in the first and a related-tools pointer in the second. No redundant content.

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 the tool's simplicity (one parameter, output schema present, robust annotations), the description is sufficient and includes a helpful related-tools note. Complete for its context.

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 schema fully describes the single domain parameter with 100% coverage. The description does not add parameter details beyond the schema, 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 clearly states the tool returns Google Safe Browsing status for a domain, using a specific verb and resource. It also names related tools (whois, backlink_summary) to help distinguish it from siblings.

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 names related tools but does not explain when to prefer safety over whois or backlink_summary. There is no explicit usage context or exclusion criteria, so only an implicit sense of purpose guides selection.

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 all annotation hints set to false, the description carries the transparency burden. It adds important behavioral context: encrypted storage, per-user isolation, and the requirement for memory-enabled accounts. It also implies automatic execution timestamps. It does not describe action-specific side effects (e.g., overwriting on set) or idempotency, but the exclusions and storage details are valuable beyond the annotations.

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 sentences with no wasted words: first sentence states purpose, second lists exclusions, third gives requirements. It is front-loaded and structured logically, making it easy for an agent to parse quickly. Every sentence adds distinct value without redundancy.

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 the tool has 5 parameters, 0 required, an action enum, and an output schema, the description covers the essential context: purpose, exclusions, and access requirements. It does not explicitly describe the CRUD nature (get/update/delete) beyond the schema, but the output schema and parameter schema fill that gap. The description is complete enough for an agent to understand the tool's role and constraints.

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 baseline is 3. The description does not add per-parameter meaning beyond the schema; it mentions 'strategy text' and 'result' but does not clarify interaction between parameters (e.g., id required for update/delete) or constraints like maximum length, which the schema already documents. The description's value is contextual rather than parameter-specific, so a 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 clearly states the tool's function: 'Store user-authored strategy text, execution timestamps, and the most recent result in encrypted per-user storage.' This specific verb+resource pair distinguishes it from siblings like 'preferences' and other domain tools. The exclusions ('does not provide presets, define opportunities, choose domains, or execute a workflow') further clarify its limited scope, aligning with the tool's role as a state storage utility.

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 provides usage context by stating exclusions ('does not provide presets, define opportunities...') and a prerequisite ('Requires a registered account with memory enabled'). This helps an agent know when NOT to use it, but it does not explicitly say 'use this when you need to persist strategy state' or compare to alternatives. Given the absence of similar sibling tools, the exclusions are sufficient 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds behavioral context by specifying the return shape (per-TLD status and aggregate counts) and the scope (core TLDs), which goes beyond the annotations. It doesn't contradict annotations.

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 two sentences, front-loaded with the action, and includes a compact pointer to related tools. Every sentence contributes value; no redundancy or filler.

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?

This is a simple read-only tool with one parameter and an output schema present. The description sufficiently communicates what it does and what it returns, and the output schema handles detailed return values. The mention of 'core TLDs' and aggregated counts completes the contextual picture without being verbose.

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 schema description for the single 'prefix' parameter is highly detailed ('Keyword without extension, e.g., openai'), providing 100% coverage. The tool description adds no parameter-level detail, so the schema carries the full burden. 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 clearly states the tool checks registration of a prefix across core TLDs and returns per-TLD status plus aggregate counts. It uses a specific verb ('check') and resource ('prefix across core TLDs'), and explicitly names related tools (bulk_tld, available), distinguishing its cross-TLD scope from bulk and single-TLD alternatives.

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 provides clear context for when to use this tool: when you need to see how a prefix is registered across multiple TLDs. It names related tools (bulk_tld, available) as alternatives, but stops short of explicit 'use this instead of X when...' guidance. Still, the purpose and related tools give enough signal for appropriate selection.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, indicating a safe read operation. The description adds little beyond that—'related metrics' is vague, and 'chosen period' is inaccurate given the parameter schema. It does not contradict the annotations, but also does not provide additional meaningful behavioral disclosure.

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 two short sentences: one for the core purpose and one pointing to a related tool. It is front-loaded and every word earns its place, with no unnecessary elaboration 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 the tool's simplicity (2 optional params, output schema present) and strong annotations, the description is minimally viable. However, it lacks details about what 'related metrics' include, how the ranking is ordered, and the 'chosen period' phrase creates confusion because no period parameter exists. This gap is significant enough to prevent a higher score.

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 has 100% coverage, as both 'type' and 'limit' have descriptions. The description does not add meaning beyond the schema and actually introduces a 'chosen period' concept that does not map to any parameter. Since the schema already explains the parameters, the baseline of 3 is appropriate, but no additional semantic value is provided.

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 ranks TLDs by registration volume, which is a specific verb and resource. It also mentions 'related metrics' and points to tld_trends as a sibling, providing some differentiation. However, the phrase 'over a chosen period' is misleading because the type parameter only allows 'newly' (today) or 'active' (total) with no actual date range selection.

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 only says 'Related: tld_trends,' which implies an alternative exists but does not explain when to use tld_rank versus tld_trends. No explicit conditions, prerequisites, or exclusions are given. The usage context is thus implied rather than clearly stated.

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?

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the safe read nature is disclosed. The description adds behavioral context about the two modes (active vs newly registered, single vs compare) and clarifies that data is returned, which goes beyond the schema. No contradictions found.

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 two sentences, front-loaded with the core purpose and immediately followed by related tools. Every sentence earns its place, with no redundancies or filler.

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?

With a complete schema (100% parameter coverage) and an output schema present, the description does not need to explain return values. It adequately covers the main usage patterns. However, it does not explicitly state parameter dependencies (e.g., action='data' expects tld, action='compare' expects tlds), though the schema does cover this. This minor gap prevents a 5.

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 all five parameters are already documented with clear descriptions. The description adds some context by linking 'active-total or newly-registered' to the type parameter and 'compare multiple' to action, but this is minimal added value over 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 clearly states the tool returns registration trend data for a TLD over time or compares multiple TLDs, specifying the two modes (active-total vs newly-registered). This distinguishes it from siblings like tld_rank and keywords_trends by focusing on registrations.

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 clear context for when to use the tool (for TLD registration trends, either single or comparison). It mentions related tools (tld_rank, keywords_trends) but does not explicitly state when not to use them or provide exclusions, stopping short of a 5.

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?

Annotations already cover readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds meaningful behavioral context: it details the output fields (variant domain, mutation type, prefix TLD count, registration date) and explains the permutation generation process. It also clarifies that it checks registration status, which is a read-only behavior consistent with the annotations. No contradictions or missing side effects are apparent.

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 concise and well-structured: it opens with the core purpose, then lists generated variant types, then result fields, then use cases, and ends with related tools. Every sentence provides unique value; there is no fluff or repetition. The front-loaded purpose ensures immediate understanding.

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 the tool's complexity (many mutation types and output fields), the description fully covers what it does and what it returns. The output schema exists and the description explicitly mentions the key return fields, so no need to describe the return format further. It also lists related tools and use cases, making it complete for an AI agent to decide when 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?

Schema coverage is 100%, with the single parameter 'domain' well-described in the schema ('Domain to scan (e.g. example.com)'). The description does not add new meaning to the parameter itself, but it reinforces that the domain is the input for generating permutations. Since the schema fully documents the parameter, a baseline score 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 clearly states the tool's function: 'Generate typosquat permutations for a domain and check which variants are registered.' It lists specific mutation types (omission, transposition, keyboard-adjacent replacement, etc.), which distinguishes it from related lookup tools like whois, dns, and ns_reverse. The verb 'Generate' and 'check' with resource 'domain' is specific and 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?

The description provides clear use cases: 'Use for brand protection, phishing detection, and defensive registration planning.' It also lists related tools (nrds, ns_reverse, dns, whois, safety), which suggests alternatives for other tasks. However, it does not explicitly state when not to use this tool or differentiate it from those related tools beyond the mutation-generation focus.

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?

The annotations already mark this as read-only, idempotent, and non-destructive, so the bar for additional disclosure is lower. The description adds useful context by specifying that it returns domains 'still available for registration' and lists concrete pattern shapes, which behaviorally clarifies the result set. It does not mention pagination or rate limits, but the schema parameter descriptions cover some of that (e.g., page depth).

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 consists of just two sentences: the first clearly states the tool's core function and any pattern caveats, and the second names related tools. It is front-loaded with the main purpose, contains no filler, and 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?

With an output schema present, the description does not need to explain return values. The tool has 8 optional parameters, and the description gives enough context about its scope (short .ai domains, pattern filtering, availability check). It could be more explicit about the relationship to 'available' and 'bulk_available', but overall it is complete for a read-only search 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 description coverage is 100%, so every parameter already has a description (type, sort, exclude, keyword, etc.). The tool description does not add extra meaning beyond what the schema provides; it only hints at pattern types (CVCV, CVCC) which are already enumerated in the type parameter. Thus, 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 uses a specific verb+resource construction: 'Search unregistered short .ai domains by pattern' and details the pattern types (CVCV, CVCC, other 3-4 letter shapes). It also names related tools (available, bulk_available), which helps distinguish it from siblings that likely perform broader availability checks.

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 usage through its purpose statement and the 'Related: available, bulk_available' line suggests alternatives, but it does not explicitly state when to choose this tool over the related ones. There is no clear when-not-to-use guidance or differentiator beyond the pattern-search focus.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds meaningful context by enumerating the exact categories returned (tier, usage, rate limits, quotas) and notes that Monitor and Strategy quotas are 'stateful,' which is useful behavioral insight beyond the annotations.

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 contains zero filler and conveys the full purpose. Every element 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?

Given the zero-parameter complexity and the presence of an output schema, the description sufficiently covers what the tool returns. No further details about return value structure are needed, and the description is complete for an agent to select and invoke the tool correctly.

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 has zero parameters, so the description does not need to explain any. Baseline 4 is appropriate because no parameter guidance is required.

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 'Return' and clearly identifies the resource as 'current account tier, per-tool-group usage, rate limits, and stateful Monitor and Strategy quotas.' This precisely distinguishes the tool from siblings like 'monitor' and 'strategy' by framing it as the quota/usage overview.

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 usage for checking account-level limits and quotas but provides no explicit 'when to use' vs alternatives or exclusions. An agent can infer the use case, but the tool does not state when it should be preferred over other information-gathering tools.

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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds value by enumerating the data fields returned (registrar, dates, status, nameservers), providing useful context beyond the annotations.

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 two concise sentences, front-loaded with the action and key data fields. The 'Related' line is brief and non-redundant, with no wasted words.

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 a strong annotation profile and an output schema, the description adequately covers purpose and data scope. Minor gap is the lack of explicit usage guidance beyond the related-tools hint.

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%, with the sole parameter 'domain' already described as 'Domain name'. The description adds no additional parameter-level detail, so it does not improve upon the schema's clarity.

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 returns WHOIS/RDAP registration data for a domain, listing specific data elements (registrar, dates, status, nameservers). This distinguishes it from siblings such as dns and safety, which likely handle other aspects.

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 provides only a brief 'Related: dns, safety' line, which hints at related tools but does not explicitly state when to use this tool versus alternatives. It implies usage for registration data but lacks clear exclusion or selection guidance.

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