multi-format-transaction-parser
Parse and consolidate financial transaction data across multiple CSV formats and years
Best use case
multi-format-transaction-parser is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Parse and consolidate financial transaction data across multiple CSV formats and years
Teams using multi-format-transaction-parser should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/multi-format-transaction-parser/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How multi-format-transaction-parser Compares
| Feature / Agent | multi-format-transaction-parser | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Parse and consolidate financial transaction data across multiple CSV formats and years
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Multi-Format Transaction Parser When analyzing financial data spanning multiple years/sources, transaction CSV formats often differ (column names, date formats, transaction types). Build an adaptive parser that detects format variations, handles schema mismatches gracefully, and consolidates into a unified dataset. Use pandas with conditional logic to map columns by position or fuzzy matching, then validate totals across years to catch parsing errors.
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