Register a developer account on AI Skill Store. API key is issued after email verification. / 개발자 계정 등록.
이메일 인증 후 API 키가 발급됩니다 (보안을 위해 즉시 발급되지 않음).
Args:
username: 사용할 username (영문/숫자, 3자 이상, 중복 불가)
email: 인증용 이메일 주소 (필수 — 인증 링크가 발송됨)
Returns:
등록 결과 메시지. 이메일 인증 후 API 키를 받을 수 있습니다.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | |||
| username | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses a critical behavioral trait: the API key is not issued immediately and requires email verification, with a security rationale. This goes beyond basic registration semantics and gives the agent important expectations about the process.
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 structured with Args and Returns sections, and is reasonably concise. The bilingual repetition (English and Korean) is somewhat redundant for an AI agent, but it doesn't harm clarity. It is not overly verbose and the main points are 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 (2 required params, no enums/nested objects) and has an output schema, so the description does not need to explain return values. It covers the main workflow (registration, email verification, delayed API key) and parameter constraints. It is complete for the tool's complexity.
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 provides no descriptions (0% coverage), so the description must compensate. The Args section adds meaningful constraints: username must be alphanumeric, at least 3 characters, and unique; email is required for verification and receives a verification link. This fully explains both parameters' purpose and rules.
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 ('Register') and resource ('developer account on AI Skill Store'), and distinguishes this from sibling tools like upload_skill or get_skill. It also mentions the key follow-up behavior (API key after email verification), making the tool's 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 does not explicitly state when to use this tool versus alternatives or provide exclusions. However, the name and purpose make it clear this is for account registration, and the sibling tools are all different actions. Usage context is implied but not explicitly articulated.
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.
Several tool pairs overlap in purpose: check_vetting_status vs get_vetting_result both query security vetting, and get_agent_author_stats vs get_agent_identity_stats both provide agent statistics. Though descriptions are detailed and clarify differences, the similar names and overlapping functionality create potential selection confusion.
Tool names follow a consistent lowercase snake_case verb_noun pattern (e.g., search_skills, upload_skill, get_skill). Minor inconsistency exists between check_* and get_* for related status operations, but overall convention is clear.
With 18 tools, the server is moderately comprehensive, covering search, upload, download, vetting, reviews, and platform compatibility. This is slightly above the typical 3-15 well-scoped range but not excessive given the store's multi-faceted domain.
Core lifecycle is mostly covered: registration, upload, search, retrieval, download, review, and vetting. However, there are notable gaps—no update or delete operations for uploaded skills, and no method to fetch existing reviews, only post them.