Financial Education Path Designer

👤 harrylabsj 📦 v1.0.1 ⭐ 3.8 ⬇️ 653 下載
🎓 教育學習 免費

📖 技能介紹


slug: financial-education-path-designer version: "1.1.0" tags: financial-literacy, learning-path, education-planning, personal-finance, skill-development type: descriptive language: en


Financial Education Path Designer

發現更多技能外掛,請訪問7w4.net。

Overview

Designs financial education paths. This is a descriptive skill that provides frameworks and templates without executing real code.

Usage Scenarios

Scenario 1

User input: "I'm 25 and financially illiterate. Design a 6-month self-study curriculum to go from zero to competent."

Expected output: Month-by-month curriculum: Month 1 (budgeting + banking), Month 2 (debt + credit), Month 3 (investing basics), Month 4 (taxes), Month 5 (insurance), Month 6 (retirement planning) — with recommended books, YouTube channels, podcasts, and practice exercises per topic.

Scenario 2

User input: "My teenager needs a financial education path before going to college."

Expected output: 12-week pre-college curriculum covering student loans, credit cards, budgeting for campus life, part-time job taxes, basic investing, and identity-theft prevention — with parent-teen discussion guides.

Scenario 3

User input: "I need to understand real estate investing. Build me a progressive learning path."

Expected output: Staged learning path: fundamentals (REITs, leverage, cap rates) → market analysis → deal evaluation → financing → property management → scaling — each stage with specific resources, practice exercises, and competency checklist.

Scenario 4: 想學理財但不知道從哪裡開始

User input: "工作兩年了手裡有5萬塊存款一直放餘額寶,有人說買基金有人說買股票,有點懵,該從哪學起?" Expected output: 設計從零到一的理財學習路徑:第一階段(第1個月)——讀《小狗錢錢》建立財商思維,瞭解貨幣基金/債券基金/指數基金的差別;第二階段(第2-3月)——用支付寶的'幫你投'或微信的理財通做首次配置(建議50%債基+30%滬深300指數+20%貨幣基金);第三階段(第4-6月)——通過持有體驗學習市場波動,不急於追漲殺跌。推薦關注'招財大牛貓'/'這是琉璃'等本土理財公眾號學習基本概念。強調先學後投,不投不懂的東西。

Safety

  • No real code execution
  • No external API calls
  • No financial transactions
  • Informational only

Outputs

  • Structured analysis
  • Actionable recommendations
  • Next steps checklist

🤖 AI 評測

文件和安全性做得不錯,但實際功能與描述有較大差距。文件清晰、測試充分、風險提示完善,但核心的學習路徑設計功能目前只有框架而沒有真正實現細節。使用者可能無法獲得預期的那種詳細的、分階段的學習計劃。建議等開發者完善程式碼實現後再使用。

📊 多維度評分

適應性3.9
規範性4.1
有效性3.2
可靠性3.3
可信度4.9

📁 包含檔案 (8 個)

📄 ACCEPTANCE.md 399 B
📄 README.md 1.7 KB
📄 SKILL.md 2.5 KB
📄 _meta.json 152 B
📄 handler.py 4.7 KB
📄 skill-card.md 2 KB
📄 skill.json 652 B
📄 tests/test_handler.py 1.6 KB