AI Skill Store

search_skills

Search skills on AI Skill Store. Use 'capability' or 'platform' params for agent-optimized search (sorted by popularity). Returns skill name, description, downloads, rating, and trust level. / AI Skill Store에서 스킬 검색.
capability나 platform을 지정하면 에이전트 최적화 검색(인기순 정렬)을 사용합니다.

Args:
    query: 검색 키워드 (스킬 이름 또는 설명). 비워두면 전체 목록.
    capability: 능력 태그로 검색 (예: web_search, text_summarization, code_generation)
    platform: 특정 플랫폼 호환 스킬만 (OpenClaw, ClaudeCode, ClaudeCodeAgentSkill, Cursor, GeminiCLI, CodexCLI)
    min_trust: 최소 신뢰 등급 (verified > community > sandbox)
    category: 카테고리 필터 (에이전트 검색 미사용 시에만 적용)
    sort: 정렬 기준 (에이전트 검색 미사용 시에만: newest | downloads | rating)
    limit: 결과 수 (기본 20, 최대 50)

Returns:
    스킬 목록 문자열

Input Schema

TableJSON Schema

Name	Required	Default
`sort`	No	newest
`limit`	No
`query`	No
`category`	No
`platform`	No
`min_trust`	No
`capability`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the return fields (name, description, downloads, rating, trust level) and the popularity-based sorting behavior for agent-optimized search. It doesn't cover potential errors or pagination, but it's still substantive.

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

Conciseness4/5

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

The description is structured with an overview, Korean translation, and an Args block. Each line earns its place, though the bilingual repetition adds slight redundancy. Still, it's front-loaded and well-organized.

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

Completeness5/5

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

Given 7 parameters with 0% schema coverage and an output schema present, the description covers all parameters, return values, and special search modes. It is complete enough for an agent to invoke correctly without additional info.

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

Parameters5/5

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

Schema description coverage is 0%, and the description compensates fully by explaining each parameter in detail—including behavior like 'empty query returns full list' and constraints like 'sort only applies when agent search is not used.' This adds significant value beyond the default-only schema.

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

Purpose4/5

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

Clearly states 'Search skills on AI Skill Store' with a specific verb and resource. It differentiates from siblings like get_skill by focusing on search, though it doesn't explicitly name alternatives.

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

Usage Guidelines4/5

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

Provides clear guidance on using capability or platform for agent-optimized search and notes that sort/category only apply when not using agent search. However, it doesn't explicitly state when to use this tool over siblings like get_skill.

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

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TDQS

A3.8/5.0

Disambiguation3/5

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.

Naming Consistency4/5

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.

Tool Count4/5

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.

Completeness3/5

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.

Resources

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