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AI Skill Store

by io.github.garasegae

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
NameRequiredDescriptionDefault
daysNo
typeNoall
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.5/5.0
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 that the tool aggregates '0건 검색 쿼리' (zero-result queries), describes the return as a summary string with fields (query, query_type, zero_result_count, last_seen), and notes the supply-loop context. This goes beyond a generic 'get' and provides meaningful behavioral insight, though it omits details like auth or rate limits.

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 well-structured with clear Purpose, Args, and Returns sections, and it front-loads the main purpose. The bilingual text (English/Korean) is slightly redundant but not wasteful, and every sentence contributes to understanding the tool's function and parameters.

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?

The description covers the tool's purpose, usage context, parameter semantics, and return format (including each field in the output string). Even without an explicit output schema, the Returns section fully describes the return value. This is complete for a 3-parameter retrieval tool.

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?

The schema provides only names and defaults with zero descriptions, but the description's Args section fully explains each parameter: days (recent N days, default 30, max 365), limit (max count, default 20, max 100), and type (enum values 'keyword' | 'capability' | 'all'). This completely compensates for the schema's lack of descriptions.

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 the tool's purpose: 'Get the list of most-wanted skills that haven't been built yet (Supply Loop).' It uses a specific verb ('Get') and resource ('list of most-wanted skills'), and distinguishes it from sibling tools like get_skill or search_skills by emphasizing unbuilt skills. The Korean translation reinforces the meaning without adding ambiguity.

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 provides clear context for when to use the tool: 'Agents can build these to fill community demand' and explains that the list aggregates zero-result search queries, implying a demand-driven use case. However, it does not explicitly name alternatives or state when not to use this tool, so it falls short of a 5.

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

All AI Skill Store toolsInspect
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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, but check_vetting_status and get_vetting_result both deal with security vetting and could be confused. Similarly, get_agent_author_stats and get_agent_identity_stats overlap somewhat, though descriptions differentiate them.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (e.g., search_skills, upload_skill_draft, get_vetting_result). No mixed conventions or vague verbs.

Tool Count4/5

18 tools is slightly above the typical well-scoped range (3-15), but the coverage of a skill marketplace (search, browse, upload, vet, review, stats, install) justifies the count. It doesn't feel bloated.

Completeness3/5

Core workflows are covered: search, download, upload, review, and status checks. However, there is no tool to update or delete an uploaded skill, and no way to list skills uploaded by a particular author, which are notable gaps for a marketplace.

Resources