aifolimizer: Skill for Claude Code

Stock Compare (Head-to-Head)

Stage 0 - Decision Memory (load BEFORE forming any verdict)

Before fetching market data, load prior decisions on each ticker (A and B) so the verdict stays consistent across sessions:

• mcp__aifolimizer__get_ticker_decision_history with ticker=A then ticker=B (max_decisions=5) - prior actions, outcomes, reflections
• mcp__aifolimizer__get_ticker_reflection with symbol=A / symbol=B (n=3) - prior recs + realized alpha
• mcp__aifolimizer__get_cross_ticker_lessons with max_lessons=3 - portfolio-level win/loss patterns

Reconciliation rule: if a prior decision exists and your new read flips it, state explicitly WHY it changed (new data / catalyst / price move). Never silently contradict a logged decision - that drift is exactly what this prevents.

How to run

1. Call mcp__aifolimizer__get_profile - account types, capital, tax context. Frame placement recommendation at end (TFSA vs RRSP vs Non-Reg)
2. Identify two tickers from user query (Ticker A, Ticker B). If user names only one and asks "vs sector leader", pick obvious peer and state choice explicitly
3. Call mcp__aifolimizer__get_portfolio - flag which tickers user already holds, with current weight and cost basis
4. Call mcp__aifolimizer__get_fundamentals with symbols=[A, B] in one call - P/E, EPS, dividend yield, payout, market cap, analyst target, beta
5. Call mcp__aifolimizer__get_technicals with symbols=[A, B] in one call - SMA20/50/200, RSI, MACD, Bollinger Bands, trend, Minervini stage + score, 52-week context
6. Call mcp__aifolimizer__get_news_headlines for each ticker - recent catalyst differential
7. WebSearch only for: sector peer multiples, recent analyst upgrade/downgrade asymmetry, or gaps in MCP response

Investor profile

• Canadian retail investor
• Time horizons: short-term trading + long-term (10yr+) holding
• Strategy lens: confirm with user (growth / income / value); default to growth if unstated
• Account types and capital: always read from get_profile - never hardcode