유튜브 계정 정보 수집
crawl_youtubeCollect a YouTube channel profile and its latest uploaded videos. 유튜브 계정(채널) 정보와 최근 게시한 동영상 정보를 수집해 반환합니다. [호출당 40포인트]
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| user_id | Yes | 수집할 유튜브 사용자(채널) 아이디 (예: CNN) |
crawl_youtubeCollect a YouTube channel profile and its latest uploaded videos. 유튜브 계정(채널) 정보와 최근 게시한 동영상 정보를 수집해 반환합니다. [호출당 40포인트]
| Name | Required | Description | Default |
|---|---|---|---|
| user_id | Yes | 수집할 유튜브 사용자(채널) 아이디 (예: CNN) |
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.
Add one secure layer between your agents and this server.
Each tool targets a distinct action or resource: YouTube has crawl and download; Google has three separate search modes; URL tools cover HTML fetching, screenshots, and similarity; and network tools are all unique lookups. No two tools overlap in purpose, making selection unambiguous.
The naming is generally readable but mixes conventions: some use verb_noun (crawl_youtube, reverse_ip), others use noun_noun with brand prefixes (google_search, url_screenshot), and a few are single conventional words (location, whois, nslookup). While not chaotic, there is no uniform verb_noun pattern across the set.
With 13 tools, the server is well-scoped for a web research/investigation toolkit. Each tool covers a distinct aspect of web data collection and DNS/IP analysis, and none feel redundant or unnecessary.
The toolkit provides comprehensive coverage for web research: searching (web, image, reverse image), YouTube data collection, URL content analysis, and a full suite of DNS/IP/WHOIS tools. There are no obvious dead ends or missing operations for its intended purpose.