korean-synthetic-consumer
hackinggrowth/korean-synthetic-consumer
This skill creates a Korean synthetic consumer and persona panel using demographic data from Hugging Face to evaluate products, messages, and interview scripts. It provides structured report templates and Python helper scripts for rapid market hypothesis generation.
7 6MITUpdated 2026-04-29
73
GoodOverview
Designed for marketers, founders, and product teams, this skill builds tailored Korean consumer panels to pressure-test messaging, assess product-market fit, and map potential objections. It includes offline capabilities using example datasets alongside optional Hugging Face dataset integration, helping teams spot blind spots and refine outreach before spending budget on real-world recruiting.
Capabilities
- ▸Persona sampling from local JSON examples or Hugging Face datasets
- ▸Multi-persona panel generation with diverse demographic traits
- ▸Structured markdown report generation and prompt scaffolding
- ▸Anti-bias rule enforcement (e.g., ensuring skeptical viewpoints are included)
Best for
Testing landing page copy, sales pitches, and outreach messages for Korean markets, Assessing product concept fit, adoption triggers, and willingness-to-pay (WTP), Mapping potential budget, trust, and workflow objections before sales calls or proposals, Generating non-leading real-world customer interview questions based on synthetic feedback
Works with
Claude CodeCursorGitHub CopilotOpenCode
Evoa Score breakdown= Σ (score × weight)
73Task usefulness20%77 → +15.4
実タスクにどれだけ役立つか（機能の豊富さ・用途の明確さ）。 — AIによるcapabilities/use-cases解析
Code quality15%90 → +13.5
実装・指示の品質。 — AIによるSKILL.md/README解析
Maintenance15%70 → +10.5
リポジトリがどれだけ活発に保守されているか。 — GitHub 最終push日時の新しさ
Documentation12%46 → +5.5
ドキュメントの充実度・分かりやすさ。 — README/独自要約の情報量
Security15%80 → +12.0
危険・不審な挙動が無いか。 — AIによるセキュリティレビュー
Originality10%85 → +8.5
ありふれたラッパーではない独自性。 — AIによる独自性判定
Popularity8%33 → +2.6
コミュニティの採用度。 — GitHub Stars/Forks（対数スケール）
Compatibility5%100 → +5.0
対応AIエージェントの広さ。 — AIによる対応エージェント判定
Weighted total73.1 / 100
ライセンス不明/制限あり（Red）のSkillは総合スコアに0.85倍の補正を適用します。 ランキングはこのScoreのみで決まり、広告で変わりません。 算出方法の詳細 →
Security considerations
Relies on local Python scripts and standard library execution with optional internet access for Hugging Face data fetching. Users must ensure sensitive enterprise or consumer data is not accidentally committed to version control.
Categories
Summary and analysis are original content generated by AI Skills Rank. The skill's source text is not reproduced here — view it on the linked repository.