Stock Data

Assemble a reusable research snapshot for: $ARGUMENTS

Overview

Implementation status: code-backed
Local entry script: <bundle-root>/stock-data/run.py
Primary purpose: build a structured one-symbol research packet with market features and non-price context, without collapsing into a full thesis memo or order frame
Workflow stages: stage 2 Data Collection & Quality Assurance, stage 3 Data Cleaning & Normalization, and stage 4 Feature Engineering & Signal Construction
Local executor guarantee: build a persisted packet containing quote context, levels, indicators, fail-open fundamentals, and raw blocks for downstream reuse

The user wants a reusable structured snapshot rather than a prose-heavy report.
The caller needs a canonical artifact that other skills can inspect, compare, or extend.
The user wants market features plus best-effort fundamental context without the fuller memo discipline of analysis.