Research Workflow Skill

Workflow Steps

1. Scope Definition — Clarify research objectives, timeframe, and deliverable format
2. Data Collection — Gather intelligence from multiple sources with temporal qualifiers
3. Source Validation — Flag market data older than same-day, economic data older than 30 days
4. Analysis — Apply analytical frameworks to collected data
5. Synthesis — Produce research summary with confidence levels and data gaps
6. Handoff — Package findings for downstream analysis (quant, strategy)

Tools Integration

• screener_cli.py

  — Multi-pattern technical screening (8 patterns)

• moving_averages_cli.py

  — Trend identification (SMA/EMA/WMA/HMA)

• momentum_cli.py

  — Confluence analysis (RSI, MACD, Stochastic, Williams %R, ROC)

• volatility_cli.py

  — Regime analysis and opportunity assessment

• data_validator_cli.py

  — Data integrity verification (100% quality required)

• itc_risk_cli.py

  — Market-implied risk scores for supported tickers

Requirements

• ALL web searches MUST include temporal qualifiers using current date context
• Separate verified data from assumptions with confidence levels
• Cite all sources with START/END tags and precise timestamps
• Flag data gaps relevant to downstream analysis