AI Skill Store

get_most_wanted

Get the list of most-wanted skills that haven't been built yet (Supply Loop). Agents can build these to fill community demand. / 미공급 수요 스킬 목록 (Most Wanted).
0건 검색 쿼리를 집계한 결과 — 여기 올라온 스킬을 만들어 업로드하면 즉시 다운로드 수요 있음.

Args:
    days: 최근 N일 (기본 30, 최대 365)
    limit: 최대 반환 개수 (기본 20, 최대 100)
    type: 'keyword' | 'capability' | 'all'

Returns:
    수요 랭킹을 요약한 문자열. 각 항목: query, query_type, zero_result_count, last_seen.

Input Schema

TableJSON Schema

Name	Required	Default
`days`	No
`type`	No	all
`limit`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.4/5.0

Behavior4/5

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

No annotations are provided, so the description must carry the burden. It discloses the data source (aggregated zero-result search queries), the return format (a summary string with fields), and the practical implication (building these skills yields demand). It doesn't explicitly state side effects, but 'get' implies read-only, and the disclosure is strong.

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 bilingual, which adds some redundancy but remains well-organized with purpose, arguments, and return sections. Every piece contributes useful information, though the English-Korean repetition could be trimmed without losing meaning.

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

Completeness4/5

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

For a simple list retrieval tool with 3 optional parameters and a string return, the description provides sufficient detail about inputs, output fields, and purpose. It does not mention error handling or ordering, but these are minor given the context.

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%, but the description fully compensates by listing each parameter with defaults and constraints: 'days: 최근 N일 (기본 30, 최대 365)', 'limit: 최대 반환 개수 (기본 20, 최대 100)', and 'type: 'keyword' | 'capability' | 'all''. This adds meaning beyond the schema's defaults.

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

Purpose5/5

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

The description clearly states 'Get the list of most-wanted skills that haven't been built yet (Supply Loop)' with a specific verb and resource. It differentiates itself from siblings like get_skill or search_skills by focusing on demand and zero-result queries.

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?

The context of when to use this tool is clear: agents should use it to discover skills to build and fill community demand. However, it does not explicitly name alternatives or exclusion conditions, but the unique purpose is evident.

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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