AI Skill Store

get_most_wanted

Read-onlyIdempotent

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

Name	Required	Description	Default
`days`	No	Look-back window in days, 1-365. Default 30.
`type`	No	Which zero-result queries to include, one of: keyword \| capability \| all. Any other value falls back to all.	all
`limit`	No	Maximum number of ranked items to return, 1-100. Default 20.

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedNov 2, 2026

addedInput schema / properties / days / description

Added value: +"Look-back window in days, 1-365. Default 30."

addedInput schema / properties / limit / description

Added value: +"Maximum number of ranked items to return, 1-100. Default 20."

addedInput schema / properties / type / description

Added value: +"Which zero-result queries to include, one of: keyword | capability | all. Any other value falls back to all."

AddedApr 19, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so safety is covered. The description adds genuinely non-structured context: the list is derived from aggregated zero-result queries, meaning freshness and demand are real signals rather than static catalog data. It stops short of saying how often the aggregation refreshes.

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

Conciseness3/5

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

The purpose is front-loaded, which is good, but the entire description is duplicated in English and Korean and then followed by an Args section that re-states the three schema parameters verbatim. Those sentences do not earn their place against already-structured data.

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?

An output schema exists, so return values need not be explained, and the parameter space is fully covered by the schema. Combined with annotations covering the read-only profile, the definition is sufficient to call the tool correctly; only the follow-up workflow (where the built skill gets uploaded) is left implicit.

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

Parameters3/5

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

Schema description coverage is 100%, and the Args block simply restates days, limit and type with their defaults — the schema is actually tighter (1-365, 1-100 vs '최대 365'). No semantics beyond the schema, so the baseline 3 applies.

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 first sentence states a specific verb and resource ('Get the list of most-wanted skills that haven't been built yet') and the following Korean line explains the data's origin: an aggregation of zero-result search queries. That provenance detail makes the tool unmistakable against siblings like search_skills or list_categories.

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 description tells the agent what to do with the output — 'Agents can build these to fill community demand' and that uploading such a skill would meet immediate download demand, which implicitly points to upload_skill. It gives clear context but never names an alternative tool or a when-not-to-use condition.

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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