APICK Web

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds the per-call point cost ('[호출당 40포인트]') as useful operational context, but does not disclose return format, error behavior, or rate limits, which would add further 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 and front-loaded with the core purpose in English, followed by a Korean translation that may aid multilingual usage. The duplication is slightly redundant but not excessive, and the point-cost note is useful. Overall, it is appropriately sized.

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

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

For a tool with a single required parameter, no output schema, and simple scope, the description adequately conveys that the return includes a channel profile and recent videos. It lacks detailed return-field documentation, but the absence of nested objects and the annotations provided make this sufficient for basic use.

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% with a single parameter `user_id` already meaningfully described as '수집할 유튜브 사용자(채널) 아이디 (예: CNN)'. The tool description adds no additional parameter semantics beyond the schema, so the baseline score 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's function: 'Collect a YouTube channel profile and its latest uploaded videos.' This is a specific verb+resource combination that distinguishes it from sibling tools like download_youtube_video, which focuses on downloading rather than collecting metadata.

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 no explicit guidance on when to use this tool versus alternatives. It does not mention that download_youtube_video should be used for downloading, nor does it state any prerequisites or contexts where this tool is preferred. Usage is only implied by the tool's stated purpose.

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 the annotations (readOnlyHint, openWorldHint), the description adds useful behavioral details: it returns MP4 format, fails for non-public videos, and mentions a per-call cost of 3 points. This enriches the agent's understanding of side effects and failure modes without contradicting 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 concise, with the core action front-loaded in the first sentence. It includes a bilingual repetition for clarity and a cost note, but every sentence serves a purpose. No unnecessary 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?

For a simple tool with one parameter and no output schema, the description adequately informs the agent of what to expect ('return it as an MP4 file') and key constraints (public availability, failure on private/blocked). Minor gaps exist on how the file is returned (e.g., URL vs. binary), but overall it is sufficient for a low-complexity 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?

The input schema already fully describes the single parameter 'url' with an example (100% schema coverage). The description adds no additional parameter semantics, so the 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: 'Download a publicly available YouTube video and return it as an MP4 file.' It identifies the specific verb (download), resource (YouTube video), and output format (MP4), distinguishing it from sibling tools like crawl_youtube or google_search.

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 ('publicly available') and notes failure for private/blocked posts, but does not explicitly state when to prefer this tool over alternatives or provide exclusions. It lacks explicit guidance such as 'Use crawl_youtube for metadata extraction' but the name and context make the primary use clear.

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 the readOnlyHint and openWorldHint annotations, the description discloses the return format (image URL, source link, title), pagination via page, and a per-call cost of 5 points. This adds meaningful behavioral context without contradicting 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 concise and front-loaded with an English summary, followed by a Korean explanation and cost note. Every sentence adds value, with no fluff 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 two-parameter search tool without an output schema, the description covers the purpose, return fields, pagination, and cost. Combining this with readOnly and openWorld annotations makes the tool fully specifiable.

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 repeats keyword semantics and explains page usage ('결과 페이지를 넘겨 가며'), but does not add meaning beyond the schema's own descriptions.

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 performs Google image search by keyword and specifies the return fields (image URL, source link, title). This distinguishes it from sibling tools like google_search (general web search) and google_lens_search (image-based search).

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 that this tool is for keyword-based image searches, which implies when to use it. It mentions the page parameter for pagination but does not explicitly name alternatives or exclusions, so it misses the top score.

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

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

Annotations already declare readOnlyHint=true, and the description adds useful behavior context: allowed image types, cost per call ('[호출당 40포인트]'), and output types (web pages, labels). It does not contradict the annotations. Minor issue: 'upload an image' could be taken literally while the schema requires a URL, but the schema clarifies this.

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 short but redundant: it repeats nearly identical info in English and Korean. Front-loaded in English, but the bilingual duplication is wasteful and could be trimmed to a single language for clarity.

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 single-parameter tool with no output schema, the description covers purpose, input constraints, cost, and output types. It lacks explicit error-handling notes, but overall it is complete enough for an agent to invoke 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?

Schema coverage is 100%, so the description adds little beyond schema. It reiterates that only image formats are allowed and mentions 'upload', but provides no new syntax or format details. 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 explicitly states 'Reverse image search' and specifies the action: 'upload an image and get visually matching web pages and labels.' This clearly differentiates it from sibling tools like google_image_search (text-based image search) and google_search (web search).

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 usage context is implied ('upload an image') but there is no explicit guidance on when to choose this tool over alternatives or when not to use it. The distinction from google_image_search is left implicit.

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 openWorldHint=true, so the safety profile is covered. The description adds valuable context beyond the annotations: it explicitly states the result fields (link, title, snippet), clarifies pagination behavior, and discloses a cost per call ('5 points'). This goes beyond what the annotations indicate.

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 with the core purpose, followed by a Korean translation and a cost note. The bilingual redundancy is somewhat unnecessary for an AI agent but not wasteful. The essential information is present in a compact form.

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 relatively simple tool with no output schema, the description covers the key aspects: what it returns (link, title, snippet), pagination support, and cost. It does not mention error handling or rate limits, but given the low complexity and presence of annotations, the description is adequately complete for a search operation.

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 provides descriptions for both parameters (keyword and page), so the schema coverage is 100%. The description only reiterates that 'page' is used to navigate results, which is also in the schema. The description adds no new parameter semantics beyond the schema's own documentation.

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 verb ('return') and resource ('web search results') with specific output fields (link, title, snippet). It is distinguished from sibling search tools like google_image_search and google_lens_search by explicitly mentioning 'keyword' and 'web search results', which differentiates it from image-based searches.

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 does not provide any guidance on when to use this tool versus alternatives such as google_image_search or google_lens_search. It only mentions pagination usage, which is a how-to detail, not a selection criterion. There is no explicit 'use this for text searches' or 'do not use for images' statement.

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 openWorldHint=true, and the description adds a cost per call ([호출당 100포인트]) and the scope constraint that subdomains are not tracked. This goes beyond the annotations, though it does not describe the return format or pagination.

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 short and front-loaded with the primary action, but the Korean sentence largely duplicates the English version. The scope note and cost are valuable, but the redundancy could be trimmed without losing meaning.

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 read-only lookup tool, the description covers purpose, scope, and cost, which is sufficient for basic invocation. It does not detail the response format, but with no output schema and low complexity, this is a minor gap.

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 covers the only parameter 'domain' with an example, and the description adds the semantic constraint that the domain should be a top-level domain (최상위 도메인 기준), which is not present in the schema's own description. This helps the agent provide valid inputs.

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 does a lookup of historical IP address changes for a domain. It further specifies that it operates on top-level domains and excludes subdomains, which distinguishes it from sibling tools like nslookup (current DNS) and whois (registration data).

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 use: it is for historical IP changes and is scoped to top-level domains, explicitly noting subdomains are not tracked. It does not explicitly name alternative tools for current IP lookups, so it stops short of a full when/not-when guide.

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 openWorldHint=true. The description adds useful behavioral context: it notes that 'if a domain is entered, it finds the IP and returns the location,' and it discloses the cost ('30 points per call'). This goes beyond the annotation info without contradicting it.

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 overall but contains redundancy: the English and Korean sentences repeat essentially the same information. The unique details (domain resolution behavior and cost) are valuable, but the duplicated sentence could be trimmed for tighter structure.

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 single-parameter, read-only tool with no output schema, the description adequately covers what the tool does, its input behavior, and cost. It does not detail the exact return format (e.g., country, coordinates), but this is not critical for basic usage and is somewhat covered by the phrase 'geographic info.'

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 covers the single 'address' parameter with a description ('Domain or IP to search'). The tool description enhances this by explaining that for domains, the IP is first resolved before returning the location, adding meaningful input semantics that the schema alone does not provide.

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: 'Look up the geographic location of a domain or IP address.' It uses a specific verb and resource, distinguishing it from sibling tools like nslookup, whois, and ip_history which focus on DNS, reverse IP, or history rather than geolocation.

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 use for geographic lookup but does not explicitly state when to use this tool versus alternatives like reverse_ip or nslookup. It provides some context (domain resolution) but lacks exclusions or explicit comparison to sibling 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=true, but the description adds valuable context: 'currently registered' aligns with openWorldHint (live data), non-domain input returns an error, and a per-call point cost is disclosed. These behavioral traits go 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 compact and front-loaded with the primary purpose, followed by error behavior and cost. It is bilingual, creating slight redundancy, but every element earns its place without unnecessary verbosity.

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 tool with no output schema, the description covers the purpose, expected input format, error handling, and cost. It clearly communicates the return type (list of IP addresses), making it complete for effective 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?

The input schema already describes the 'domain' parameter with an example (apick.app), so baseline is 3. The description adds meaning by clarifying that non-domain values will cause an error, which is a validation rule not present in the schema. This extra context raises the score above baseline.

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: 'Resolve a domain name to its currently registered IP addresses (DNS lookup).' It specifies the verb and resource, and the input validation note distinguishes it from sibling tools like reverse_ip (IP-to-domain resolution).

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 use for domain-to-IP resolution but does not explicitly mention when to use it over alternatives such as reverse_ip or whois. The note about non-domain input returning an error provides some usage context, but no explicit when-not-to-use guidance is 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 declare readOnlyHint and openWorldHint, so safety is established. The description adds useful context: input format restriction and a per-call point cost ('[호출당 100포인트]'), which is a form of rate-limit disclosure. No contradictions 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 composed of two brief, purposeful sentences (English and Korean) plus a format/cost note. It front-loads the main action, contains no filler, and every clause adds 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 simple one-parameter read-only lookup tool, the description, annotations, and schema together provide sufficient context including the operation, parameters, and cost. It does not specify the output format, but given the tool's simplicity and available annotations, this is not a critical gap.

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 'ip' parameter already described with an example. The description adds value beyond the schema by explicitly stating that only IP address format is accepted ('IP 주소 형식만 허용됩니다'), which is a constraint not present 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?

'Reverse IP lookup: list domains that have been hosted on a given IP address' uses a specific verb ('list') and resource ('domains hosted on a given IP'). This clearly distinguishes it from sibling tools like nslookup or whois, and the Korean title confirms the purpose.

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 the action and format constraint ('IP 주소 형식만 허용됩니다') but does not explicitly state when to prefer this over alternatives like ip_history or nslookup, nor what would make a different tool more appropriate. Context is clear but no exclusions or alternatives are mentioned.

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 provide readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds behavioral details beyond annotations: it returns *rendered* HTML (implying JS execution) and explicitly notes JavaScript rendering support, plus a cost per call. This provides useful context without contradicting 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: two short sentences (one in English, one in Korean) plus a cost note. The main action is front-loaded, the JavaScript capability is a key differentiator, and the cost is practical information. 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 simple one-parameter tool with full schema coverage, good annotations, and no output schema, the description is largely complete. It explains the return value (HTML source), a key capability (JS rendering), and cost. It does not cover error handling or redirects, but these are not essential given the tool's simplicity.

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 'url' parameter with an example, so the baseline is 3. The description does not add extra parameter-specific semantics beyond restating that a URL is entered. It does imply the URL can point to any web page (including dynamic ones), but that is not a significant extension of the schema's meaning.

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 fetches a web page and returns its rendered HTML source. The specific verb-resource pairing (fetch + web page HTML) distinguishes it from siblings like url_screenshot (image) and url_similarity (similarity). Mentioning JavaScript rendering further differentiates it from a simple HTML fetcher.

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, particularly for pages that require JavaScript rendering ('자바스크립트 렌더링이 필요한 페이지도 처리됩니다'). It does not explicitly name alternatives or exclusions, but the context of extracting HTML is well established, and the cost note adds practical 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 and openWorldHint=true, so the safety profile is known. The description adds useful context such as the output format (JPEG) and the per-call cost (5 points), but it does not disclose potential caveats like viewport size, full-page vs. visible area, or rendering delays.

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 short and the key information is front-loaded. However, the English sentence and its Korean translation say essentially the same thing, making the second sentence partially redundant. The cost note is a useful addition.

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 tool with good schema coverage and read-only annotations, the description is mostly sufficient. It states the purpose, output format, and cost. The main missing piece is explicit usage guidance, but this is not critical given the tool's simplicity.

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 url parameter is fully documented in the schema. The description mentions '입력한 URL' but adds no additional semantic detail 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 action ('Capture a screenshot'), the resource ('of a web page'), and the output ('return it as a JPEG image'). This distinguishes it from sibling tools like url_html or google_search, which serve different 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 provides no guidance on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or situations where another tool (e.g., url_html for HTML content) would be more 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=true and openWorldHint=true, so the safety profile is known. The description adds that the tool returns a similarity result and notes a cost of 5 points per call. It discloses that the tool accesses and analyzes the two pages, which is consistent with the openWorldHint. 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?

The description is two short sentences plus a cost note. The core action is stated first in English, with Korean repetition adding detail. There is no wasted text, and the length is appropriate for the tool's simplicity.

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 purpose, use case, and cost. However, there is no output schema, and the description only vaguely states 'returns similarity results' without specifying the output format (e.g., score, boolean, category). This is a minor gap for an otherwise simple tool, given annotations cover safety.

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?

Both parameters (url1, url2) are fully described in the schema with the same meaning as the tool's purpose. The description does not add parameter-level details or constraints. With 100% schema coverage, 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 'Compare two web pages and judge how similar they are' in English, with Korean elaboration. It names the specific verb (compare), resource (two web pages), and outcome (similarity). The mention of phishing/duplicate detection further clarifies its use case and distinguishes it from sibling tools like url_screenshot or google_search.

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 a concrete use case: '피싱·복제 사이트 판별 등에 활용할 수 있습니다' (can be used for phishing/duplicate site detection). It does not explicitly name alternatives or state when not to use it, but the tool's unique function among siblings makes the context clear. This earns a 4 rather than 5 because exclusions/alternatives are 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?

Annotations already indicate a read-only, open-world operation. The description adds valuable behavioral context: it specifies the data source for Korean resources (KISA/KRNIC) and discloses a cost of 100 points per call. This goes beyond the annotations and helps the agent anticipate important constraints.

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 stated immediately. It combines English and Korean to cover both audiences, and every sentence contributes either purpose, special-case behavior, or cost information. There is no redundant elaboration.

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, no output schema, read-only annotations), the description covers the essential aspects: purpose, supported input types, special data sources, and cost. It could theoretically detail output format, but for a standard WHOIS lookup this is not a significant gap.

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 already covers domain or IP input, achieving 100% coverage. The tool description enhances this by indicating that AS numbers (e.g., AS9318) are also accepted, which is not mentioned in the schema. This additional semantic information raises the value beyond 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 clearly states the tool performs a WHOIS lookup for a domain or IP address, returning registration and ownership information. It uses a specific verb ('lookup') and resource ('domain or IP'), and distinguishes itself from sibling tools like nslookup or ip_history by focusing on WHOIS registration data.

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 the tool, including special handling for Korean domains, IPs, and AS numbers via KISA/KRNIC. It does not explicitly mention alternatives or exclusions, but the scope is well-defined, so no critical guidance is missing.

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