APICK Web

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

Annotations already provide readOnlyHint=true and openWorldHint=true, and the description aligns with them by describing a collect-and-return operation with no destructive effect. It adds an operational cost note ('[호출당 40포인트]') but does not disclose output limits, the number of latest videos returned, or any external data variability beyond what openWorldHint already implies.

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, front-loads the core behavior, and includes a useful cost note. The main inefficiency is that the Korean sentence restates the English sentence, but the overall size is still appropriate for a simple tool.

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 tool with no output schema, the description adequately communicates what the tool returns: a channel profile and recent uploaded videos, plus the per-call cost. It could be more explicit about how many videos count as 'latest' or what the profile fields are, but those are minor gaps for this simple scope.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the user_id parameter already has a clear description with an example ('CNN'). The tool description adds no additional parameter-level detail, such as accepted formats or validation rules, 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 a concrete action ('Collect') and resource ('YouTube channel profile and its latest uploaded videos'), which distinguishes it from siblings like download_youtube_video or video_to_mp3. The Korean sentence reinforces the same behavior without distorting it.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies that this tool is for retrieving YouTube channel/account profile data, so an agent can infer when to use it. However, it provides no explicit guidance on when not to use it or which alternative tools to prefer, such as download_youtube_video for downloading actual videos.

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 only provide readOnlyHint and openWorldHint. The description adds meaningful behavior: output is an MP4, non-public/blocked content returns failure, and each call costs 3 points. There is no contradiction with the readOnlyHint annotation since downloading is a fetch operation.

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 core purpose. The Korean sentence duplicates the English sentence, creating slight redundancy, but the overall length is appropriate and the failure/cost notes are valuable.

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

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

For a one-parameter tool with no output schema, it adequately covers the input, the output format, and a key failure mode. It does not mention size limits or asynchronous behavior, but those are not essential for a basic call.

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 describes the single url parameter with 100% coverage, including an example. The description reinforces that the URL should point to a publicly available YouTube video but adds no additional parameter-level details beyond that.

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 ('Download') and resource ('a publicly available YouTube video') and clearly specifies the return format ('as an MP4 file'). This makes it easy to distinguish from siblings like extract_video_thumbnail or video_to_mp3.

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?

It gives a clear scope by saying the video must be publicly available and that private/blocked posts will fail. However, it does not explicitly mention alternative tools or state when-not-to-use conditions beyond the public availability constraint.

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 context: per-call cost of 20 points, pagination behavior via page, and the result structure. No contradiction with annotations is present.

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 and return fields. The bilingual English/Korean restatement is slightly redundant, but the pagination and cost details earn their place.

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

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

For a simple two-parameter read-only tool with no output schema, the description sufficiently covers return values, pagination, and cost. Minor omissions such as result count or limits prevent 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?

Schema description coverage is 100%, so the schema already documents both keyword and page. The description only restates the search behavior and pagination without adding constraints, formats, or default-value clarification beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific operation: Google image search by keyword, and lists the exact returned fields (image URL, source link, title). This clearly distinguishes it from general google_search and image-based google_lens_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?

It clearly indicates the intended use case: retrieving Google image results for a specific keyword, with page for pagination. It does not explicitly name alternatives or state when not to use the tool, so it falls 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 declare readOnlyHint=true and openWorldHint=true, covering safety and non-determinism. The description adds allowed formats and a cost note ('60 points per call'), but it does not disclose much beyond that; the 'upload an image' wording also conflicts slightly with the URL-based input in the schema. 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 compact and front-loaded with the core action, then adds format/cost constraints. The Korean sentence largely restates the English part with a slightly expanded output list, introducing minor redundancy, but overall it remains 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 one-parameter read-only tool, the description covers the purpose, a broad output description, and constraints. However, because there is no output schema, it should do more to describe what the returned labels or pages look like, and it never clarifies that the 'upload' is actually a URL reference rather than a file upload.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the schema already documents the downloadable https URL, allowed MIME types, and 50MB limit. The description only reiterates the image-format restriction and does not add meaning beyond schema, so it meets the baseline for a fully covered 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 opens with 'Reverse image search' and clearly states the action: provide an image and get visually matching web pages and labels. It is specific about verb and resource, but it does not distinguish itself from the sibling google_image_search, which appears to serve a very similar 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 use case is implied by 'reverse image search' and the Korean phrase '이미지로 검색', and the only exclusion is that only image-format files are allowed. There is no explicit guidance on when to prefer this over google_image_search, google_search, or image_similarity, so an agent must infer the appropriate context.

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 openWorldHint, so the safety profile is covered. The description adds concrete behavior: returned fields are limited to link/title/snippet, pagination is possible via page, and each call costs 5 points. 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 short and front-loaded with the core function and output shape. The bilingual repetition (English and Korean) adds minor redundancy, but it is compact and includes only useful operational notes like pagination and cost.

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 read-only lookup with full parameter documentation, the description covers the required keyword, optional page paging, and result fields. It does not detail edge cases like empty results or error formats, but those are not necessary for correct selection and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so both keyword and page are already documented in the schema. The description adds only a small amount of extra context about using page to navigate result pages, which is helpful but not essential.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('return'), a clear resource ('Google web search results'), and the exact output fields (link, title, snippet). The 'keyword' qualifier distinguishes it from sibling image/lens search tools like google_image_search and google_lens_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 through the keyword-search framing and gives pagination guidance with page, but it never explicitly says when to choose this tool over alternatives or when not to use it. Sibling differentiation is left to the reader.

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 readOnlyHint annotation already indicates a safe read operation, and the description adds beyond that: the scope constraint that subdomains are not tracked, and the cost signal of 100 points per call. It does not describe the exact return shape, but for a simple read-only lookup with annotations present, the added context is meaningful.

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 main purpose. The Korean sentence largely repeats the English sentence, which is mild redundancy, but the scope caveat and cost note are valuable additions. It is appropriately sized overall, with only one repetitive sentence keeping it from a top score.

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 with no output schema and no nested objects, the description covers the essential context: what the tool does, the domain scope, and the cost. It does not specify the output format in detail, but 'historical IP address changes' sufficiently conveys what the agent should expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already documents the single 'domain' parameter at 100% coverage with an example. The description adds important semantic nuance not in the schema: the query is based on the top-level domain and subdomains are not tracked, which tells the agent to provide an apex domain like 'apick.app' rather than a subdomain.

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: 'Look up the historical IP address changes of a domain.' This clearly distinguishes the tool from siblings like nslookup (current DNS), reverse_ip (IP-to-domain), and whois (registration info), since it is specifically about historical IP changes. The Korean sentence reinforces the same purpose without ambiguity.

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 intended use is clear: use it when you need historical IP changes for a domain. The description also gives an explicit exclusion: subdomains are not tracked and lookup is based on the top-level/apex domain. It does not explicitly name alternative tools for other lookups, but the historical vs. current distinction is implied well enough.

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, so the safety profile is covered. The description adds useful context by explaining that a domain is resolved to its IP before lookup and that each call costs 30 points; it does not detail output format or error behavior.

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?

It is short and front-loaded in English, but the Korean text largely duplicates the English sentence, creating redundancy. The cost note is useful but placed at the end; a single-language version would be tighter.

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

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

For a one-parameter, read-only lookup tool with no output schema, the description provides enough to call it: input type, resolution behavior, cost, and result concept. It could be more explicit about the return structure, but the low complexity keeps this from being a serious 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% and the address property is already described as 'domain or IP' with an example. The description adds a small amount of process information (domain-to-IP resolution) but does not materially expand parameter 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 uses a specific verb ('Look up') and resource ('geographic location of a domain or IP') and adds the domain-resolution behavior. It clearly states the tool's function but does not explicitly differentiate it from sibling lookup tools like nslookup or whois.

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?

No guidance about when to prefer this tool over nslookup, whois, or reverse_ip is provided. The closest signal is the phrase 'geographic location,' which implies a use case but never states exclusions or 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 indicate read-only and open-world behavior, and the description adds value beyond that by stating that invalid non-domain inputs return an error and that results reflect currently registered IPs. It does not mention empty-result handling or DNS resolver details, but those are minor for a simple read-only tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately short and front-loaded, with the core action in the first sentence followed by validation behavior and cost. No unnecessary background or fluff is included.

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

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

For a one-parameter, read-only DNS lookup with no output schema, the description provides enough context: what input is required, what output to expect (list of currently registered IP addresses), and what error to anticipate for invalid input. Nothing essential 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 only parameter, domain, already has 100% schema coverage with a clear description and example (apick.app). The tool description reinforces that the value must be a domain, but it does not add substantial meaning 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 uses a specific verb and resource: 'Resolve a domain name to its currently registered IP addresses (DNS lookup).' This clearly distinguishes it from sibling tools such as reverse_ip (IP-to-domain lookup) and whois (domain registration 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 use case is explicitly clear: invoke it when given a domain and needing its current IP addresses. It also states that non-domain values produce an error, which is a useful when-not-to-use signal. However, it does not explicitly mention alternatives like reverse_ip or whois.

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 that the lookup returns domain history, explicitly restricts input to IP address format, and states a per-call cost of 100 points. These details help the agent anticipate constraints and side effects 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 compact and front-loaded with the core operation in English, followed by a Korean restatement, an input constraint, and cost. The bilingual redundancy is slightly unnecessary but does not bloat the entry; every part adds functional 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?

For a single-parameter, read-only lookup with no output schema, the description covers the operation, input constraint, cost, and expected result type (list of domains). It omits pagination or error behavior, but these are not critical for a simple lookup of this nature.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the ip parameter already includes an example, so the baseline is 3. The description adds the explicit constraint that only IP address format is accepted, reinforcing input validation semantics beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Reverse IP lookup: list domains that have been hosted on a given IP address.' It clearly distinguishes from siblings like nslookup and whois by focusing on reverse mapping from IP to domains, and the Korean line reinforces the historical domain registration aspect.

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?

No guidance is given on when to use this tool versus alternatives such as ip_history, nslookup, or whois. The only usage-related statement is the input constraint 'IP 주소 형식만 허용됩니다' (only IP address format is allowed), which addresses validation rather than tool 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?

The readOnlyHint and openWorldHint annotations align with the described fetch behavior. The description adds useful context beyond annotations by disclosing JavaScript rendering support and a per-call cost, both of which help the agent anticipate behavior.

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 key purpose is front-loaded in English, and the Korean sentence repeats the same idea but is short. The JavaScript rendering and cost details are valuable. Minor redundancy prevents a higher score.

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 tool with no output schema, the description covers what it does, what it returns, dynamic rendering behavior, and cost. It is sufficiently complete for an agent to 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 single URL parameter is already fully documented in the schema with a description and example, so the description adds little beyond restating '입력한 URL.' With 100% schema coverage, the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb and resource: 'Fetch a web page and return its rendered HTML source.' It distinguishes itself from a screenshot tool by emphasizing HTML source rather than an image, though it does not explicitly name sibling 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 a use case by noting that pages requiring JavaScript rendering are handled, but it does not explicitly state when to prefer this tool over alternatives like url_screenshot or provide any 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 and openWorldHint, so the description only needs to add extra behavioral context. It adds the JPEG output format and the per-call cost of 5 points, which are useful 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 compact, with a clear English sentence, a Korean equivalent, and the cost note. The bilingual repetition is somewhat redundant but serves accessibility and remains concise overall.

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 tool, the description adequately covers input, output format, and cost. Missing details like viewport size or page-load behavior would be nice but are not essential for basic 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 covers the only parameter fully with a description and example URL, so the tool description does not need to add parameter semantics. The description adds no new meaning about the url parameter 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 (a web page URL), and the return type (JPEG image). This distinguishes it from sibling tools like url_html and url_similarity, 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 implies the tool is for capturing visual screenshots, but it does not explicitly state when to choose it over alternatives such as url_html or url_similarity. There is no exclusionary guidance or mention of when not to use it.

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 set readOnlyHint=true and openWorldHint=true, so the description does not need to restate safety. It adds the cost detail ('[호출당 5포인트]') and says a similarity result is returned, but it does not describe the output shape, scale, or whether the pages are fetched server-side. This is acceptable but not rich behavioral context.

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 core purpose in the first English sentence. There is some bilingual redundancy (the Korean sentence restates the English one), but the added use case and cost bracket are useful and keep it compact.

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

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

For a two-parameter read-only tool with annotations, the description covers purpose, use cases, and cost. However, with no output schema, it leaves the exact meaning of 'similarity result' undefined (e.g., numeric score, percentage, label), which an agent may need to interpret the response confidently.

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%: url1 and url2 are each documented as the first/second page URL to compare. The tool description adds only the general concept of page similarity, not new parameter-level meaning, so the schema carries the load and 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 states a specific operation ('Compare two web pages and judge how similar they are') with a clear resource (two page URLs), and the Korean phrase '두 사이트 페이지의 유사 여부를 분석' reinforces that it analyzes page similarity. This is distinct from sibling tools like image_similarity, which compare images rather than web pages.

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 an explicit use case ('피싱·복제 사이트 판별 등에 활용할 수 있습니다' - can be used to identify phishing/clone sites), which tells an agent when it is appropriate. It does not discuss when not to use it or mention alternatives such as image_similarity, so it stops short of full routing 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 and openWorldHint, so this is clearly a safe read operation. The description adds useful non-annotated context: Korean resources are queried via KISA/KRNIC original data, and each call costs 100 points. No contradiction exists.

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 purpose. The bilingual repetition is somewhat redundant but understandable for a Korean-facing tool, and the cost note is compactly appended without disrupting 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 single-parameter read-only lookup with full schema coverage, the description covers the accepted input types, special Korean source behavior, output purpose, and cost. It does not detail output structure or error behavior, but that is not critical for invoking this 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 schema already documents the single 'address' parameter with 100% coverage and an example. The description adds extra meaning by noting that AS numbers, such as AS9318, are also accepted and that Korean .kr/.한국 domains and domestic IPs resolve through KISA/KRNIC.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'WHOIS lookup for a domain or IP address, returning registration and ownership information.' This clearly distinguishes it from sibling tools like nslookup or reverse_ip, which serve different DNS/reverse-lookup 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 gives clear context about when to use the tool: for WHOIS registration and ownership data, including special support for Korean domains, domestic IPs, and AS numbers. It does not explicitly name alternatives or exclusion cases, but the intended use is obvious from the WHOIS-specific wording.

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