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home / skills / jeremylongshore / claude-code-plugins-plus-skills / csv-processor

csv-processor skill

/skills/19-business-automation/csv-processor

This skill helps automate csv processing tasks by providing step-by-step guidance, production-ready code, and validation for business automation workflows.

npx playbooks add skill jeremylongshore/claude-code-plugins-plus-skills --skill csv-processor

Review the files below or copy the command above to add this skill to your agents.

Files (1)
SKILL.md
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---
name: "csv-processor"
description: |
  Process csv processor operations. Auto-activating skill for Business Automation.
  Triggers on: csv processor, csv processor
  Part of the Business Automation skill category. Use when working with csv processor functionality. Trigger with phrases like "csv processor", "csv processor", "csv".
allowed-tools: "Read, Write, Edit, Bash(cmd:*)"
version: 1.0.0
license: MIT
author: "Jeremy Longshore <[email protected]>"
---

# Csv Processor

## Overview

This skill provides automated assistance for csv processor tasks within the Business Automation domain.

## When to Use

This skill activates automatically when you:
- Mention "csv processor" in your request
- Ask about csv processor patterns or best practices
- Need help with business automation skills covering workflow automation, email processing, spreadsheet operations, and business process optimization.

## Instructions

1. Provides step-by-step guidance for csv processor
2. Follows industry best practices and patterns
3. Generates production-ready code and configurations
4. Validates outputs against common standards

## Examples

**Example: Basic Usage**
Request: "Help me with csv processor"
Result: Provides step-by-step guidance and generates appropriate configurations


## Prerequisites

- Relevant development environment configured
- Access to necessary tools and services
- Basic understanding of business automation concepts


## Output

- Generated configurations and code
- Best practice recommendations
- Validation results


## Error Handling

| Error | Cause | Solution |
|-------|-------|----------|
| Configuration invalid | Missing required fields | Check documentation for required parameters |
| Tool not found | Dependency not installed | Install required tools per prerequisites |
| Permission denied | Insufficient access | Verify credentials and permissions |


## Resources

- Official documentation for related tools
- Best practices guides
- Community examples and tutorials

## Related Skills

Part of the **Business Automation** skill category.
Tags: automation, workflow, spreadsheets, email, business

Overview

This skill automates common CSV processing tasks for business automation workflows. It provides step-by-step guidance, generates production-ready code and configurations, and validates outputs against standard formats. Use it to streamline spreadsheet operations, import/export workflows, and data transformation steps in automation pipelines.

How this skill works

The skill inspects CSV structure, headers, and sample rows to infer schema and detect common issues such as delimiter mismatches, encoding problems, and inconsistent row lengths. It produces validated code snippets (Python and CLI examples), configuration templates, and actionable remediations. The skill also suggests integration points for workflow automation tools and performs lightweight validation checks against expected standards.

When to use it

  • You need to parse, validate, or transform CSV files in an automation pipeline
  • You want production-ready code snippets or configuration for CSV ingestion/export
  • You must diagnose CSV errors like encoding, delimiter, or header inconsistencies
  • You are building email or spreadsheet automation that consumes CSV data
  • You want best-practice patterns for batching, streaming, or schema validation

Best practices

  • Normalize encoding to UTF-8 and explicitly specify delimiters in configs
  • Validate headers and sample rows before bulk processing to catch schema drift
  • Use streaming processing for large files to avoid memory spikes
  • Include retry and idempotency handling in ingestion workflows
  • Log row-level errors to a separate file and continue processing valid rows

Example use cases

  • Auto-generate a Python script to validate and transform incoming CSVs for an ETL job
  • Create configuration for a workflow tool to ingest CSV attachments from email and load into a database
  • Diagnose and fix a pipeline that fails due to mixed delimiters or malformed rows
  • Convert irregular CSV exports into a normalized format for reporting
  • Design a batched processing strategy to handle multi-GB CSV files without OOM failures

FAQ

What formats and encodings does the skill support?

It handles common CSV variants (comma, tab, pipe delimiters) and recommends normalizing to UTF-8; it can detect encoding issues and suggest fixes.

Will it produce production-ready code?

Yes—examples and templates follow industry practices, but you should review and adapt them to your environment and security requirements.

How does it handle very large CSV files?

The skill recommends streaming processing, chunked reads, and batching strategies to minimize memory use and improve reliability.