Market Data

Normalize and summarize market data for: $ARGUMENTS

Overview

• Implementation status: code-backed
• Local entry script: <bundle-root>/market-data/run.py
• Primary purpose: expose the canonical one-symbol market-data pipeline without adding decision, thesis, or execution claims
• Workflow stages: stage 2 Data Collection & Quality Assurance plus stage 3 Data Cleaning & Normalization, with stage-4 feature-base preparation
• Local executor guarantee: schema normalization, required-column validation, date sorting, duplicate-date collapse, numeric coercion, indicator enrichment, and optional export

Use When

• The user wants to inspect whether a symbol’s raw price data is usable for research or backtesting.
• The user wants an enriched export that downstream skills or external workflows can reuse.
• The user wants to verify date coverage, source, row count, and the basic feature base before analysis.
• The caller needs a disciplined preprocessing step before market-analyze, stock-data, market-screen, or backtest-evaluator.