Fidelity Trade Parser

Stop Wrestling with Messy Brokerage Exports

If you've ever tried to analyze a Fidelity Accounts_History.csv, you know the frustration. Detailed trade data is buried in verbose, unstructured strings like "YOU SOLD OPENING TRANSACTION PUT (IWM) ISHARES...". This skill solves the "dirty data" problem by instantly converting messy Fidelity exports into a structured, analysis-ready format.

What it does

The Fidelity Trade Parser acts as a specialized ETL (Extract, Transform, Load) engine for your financial data. It deep-scans every row of your export to extract hidden metadata that standard CSV readers miss. Unlike a simple regex prompt, this skill is built on a robust Python architecture designed to handle the specific quirks of Fidelity's reporting, including multi-line disclaimers and complex option symbology.

• Comprehensive Parsing: Extracts ticker, strike, expiration, and option type (Call/Put) from raw text.
• Transaction Normalization: Maps complex actions to clean categories like SELL_OPEN, EXPIRED, or DIVIDEND.
• Event Handling: Tracks assignments, exercises, interest, and even foreign tax payments.
• Clean Output: Generates a flat CSV perfect for Google Sheets, Excel, or custom Python trading scripts.

Why use this skill

Manual cleanup is error-prone and time-consuming. Prompting an AI to "clean this file" often results in hallucinations or missing rows when dealing with hundreds of trades. This skill provides a deterministic, repeatable process that ensures every cent and contract is accounted for accurately.