Normalize securities data and reconcile regulatory metadata for JPX/EDINET integration.
npx skills add https://github.com/Yoshi-Dai-1/ARIA --skill stock-data-expert
Please help me install this Agent Skill. Skill: stock-data-expert Source: https://github.com/Yoshi-Dai-1/ARIA/tree/main/.agent/skills/stock-data-expert Command: npx skills add https://github.com/Yoshi-Dai-1/ARIA --skill stock-data-expert
このスキルは ARIA データの正規化と整合性管理を実現します。具体的には、5桁コードへの統一、SICC ルールに基づく親子紐付け、JPX/EDINET 間の属性解決、履歴の自己修復、異常検知のガードを提供します。
5桁正規化とリコンシリエーションを有効化して、JPX/EDINET のマスタデータを統合します。
High-intent search queries and answers about installing and using this skill.
To normalize securities data, 4-digit codes are converted to 5-digit by appending a trailing zero, resolving Excel formatting variations and enforcing strict code normalization for JPX and EDINET integration.
Securities metadata reconciliation uses a precedence-based approach where JPX Master is prioritized first, falling back to EDINET, Catalog, and historical data to resolve attributes and ensure data integrity.
Yes, using pandas, you can apply history self-healing to repair missing records and configure threshold-based anomaly detection to validate index constituent counts and code assignments.
SICC rule-based linkage connects parent and subsidiary entities during master stock alignment, applying strict precedence rules to resolve corporate relationships and ensure accurate regulatory metadata reconciliation.
IPO discovery requires registration guards to manage pending listings and generate LISTING or DELISTING events, preventing incomplete records and maintaining historical data integrity during securities reconciliation.
Anomaly guarding validates index constituent counts and code assignments against configured thresholds, but when validation fails, it triggers notifications or halts processing to prevent data corruption.
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