MCP App StoreMCP App Store
from cowork-plugins219
Generate data-driven JTBD (9 items) and three customer personas from reviews/Q&A to guide product messaging and market prioritisation.
This skill analyzes market research, product info and customer reviews to produce a structured JTBD (Jobs-To-Be-Done) set (3 functional, 3 emotional, 3 social) and cluster-based persona profiles (main + 2 backups). It can automatically map JTBD to market keywords and output priority rankings to inform messaging, naming, and channel strategy.
Use when you need to understand why customers buy (not what copy to write): JTBD discovery, persona generation from review/Q&A data, purchase driver analysis, and market-matching for e‑commerce listings. Ideal for e-commerce sellers, product teams, and marketers preparing product pages or ad messaging.
--mode jtbd produces 9 JTBD (functional/emotional/social) and market_match_priority; --mode persona chains review/Q&A collection and clustering to emit three persona objects with target_temperature metadata and a slop_review block. Fallback rules described for low-review counts and recommended chaining to downstream copy and naming skills.Designed for Claude Code / Korean-domain Claude plugins and generic LLM agent runtimes that can call external MCP tools (review_list_naver, review_list_cafe24, qna_list_cafe24).
This skill has not been reviewed by our automated audit pipeline yet.
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