Claude Skills Guide

Claude Code Batch Processing with Skills Guide

Claude Code skills transform how developers handle repetitive tasks. Instead of processing files one at a time, you can chain skills together to handle batch operations across entire directories. This guide shows you how to build efficient batch processing workflows using Claude skills. For multi-agent approaches to parallel workloads, see fan-out fan-in pattern with Claude Code subagents.

How Batch Processing Works with Skills

Skills in Claude Code are Markdown files containing specialized instructions. When you invoke a skill, Claude loads its context and applies that expertise to your current task. For batch processing, you combine skill invocation with shell commands or scripting to iterate over multiple files.

The key is understanding that skills don’t execute loops themselves—they guide Claude’s behavior while you provide the iteration mechanism through bash or scripts. This separation keeps your workflows flexible and debuggable.

Setting Up Batch Processing

Create a working directory for your batch operations:

~/batch-projects/
├── process/
│   ├── input/
│   └── output/
└── scripts/

Initialize your Claude session with the skills you need. For example, if processing design files, load the frontend-design skill alongside your processing script:

/frontend-design

Processing Multiple Files with Skill Chains

The most common batch pattern involves iterating through files and applying skill-guided transformations. Here’s a practical example processing markdown files for a documentation site:

#!/bin/bash
# batch-process-docs.sh

INPUT_DIR="./docs"
OUTPUT_DIR="./processed"

for file in "$INPUT_DIR"/*.md; do
  filename=$(basename "$file")
  echo "Processing: $filename"

  # Use claude to process each file with skill guidance
  claude -p "Apply the documentation skill to improve this markdown file.
- Fix heading hierarchy
- Add appropriate code block language tags
- Ensure links are properly formatted

$(cat "$file")" > "$OUTPUT_DIR/$filename"
done

This script uses Claude in headless mode to process each file. The documentation improvement happens through skill guidance, not manual editing.

PDF Batch Processing Example

The pdf skill handles batch document operations efficiently. Process multiple PDFs for extraction or conversion:

#!/bin/bash
# batch-extract-pdf.sh

PDF_DIR="./invoices"
OUTPUT_DIR="./extracted"

for pdf in "$PDF_DIR"/*.pdf; do
  filename=$(basename "$pdf" .pdf)

  claude -p "Using the pdf skill, extract all text content from this invoice: $pdf
Return the data as JSON with keys: invoice_number, date, total, line_items."

done > "$OUTPUT_DIR/all_invoices.json"

This extracts structured data from multiple invoices in one run. The pdf skill understands document structure and applies consistent extraction logic across files.

Code Transformation with Multiple Skills

Combine skills for complex batch transformations. This example uses the tdd skill together with a refactoring prompt:

#!/bin/bash
# batch-add-tests.sh

SRC_DIR="./src"

for file in "$SRC_DIR"/*.js; do
  echo "Adding tests to: $file"

  claude -p "Apply the tdd skill to generate unit tests for this file, then
ensure the implementation passes all tests and follows clean code principles.
File: $file

$(cat "$file")"
done

The tdd skill generates appropriate test cases while the refactoring guidance ensures the implementation meets quality standards. Running both in the prompt produces tested, clean code.

Automating Documentation Generation

The docs skill paired with batch scripts automates documentation across codebases:

#!/bin/bash
# generate-docs.sh

COMPONENTS=(
  "Button"
  "Modal"
  "Dropdown"
  "DatePicker"
)

for component in "${COMPONENTS[@]}"; do
  claude -p "Generate component documentation for this file.
Include: props table, usage examples, and type signatures.

$(cat "./components/$component.js")"
done > "./docs/components.md"

This processes multiple component files and aggregates the documentation into a single file.

Memory-Augmented Batch Processing

The supermemory skill enhances batch processing by maintaining context across iterations. When processing related files, this prevents redundant work:

/supermemory Remember: processing all API endpoint files in ./src/api/ for documentation generation

The skill tracks what has been processed and what still needs attention, making large batch jobs more efficient.

Performance Optimization Tips

Batch processing with skills runs faster when you optimize the workflow:

Parallel processing: Use GNU parallel or xargs for concurrent operations:

ls *.json | xargs -P 4 -I {} bash process-one.sh {}

Reduce skill reloads: Group similar files together to minimize context switching between different skills.

Pre-filter files: Use find or glob patterns to process only relevant files:

find . -name "*.ts" -newer last-run.txt -exec process.sh {} \;

Error Handling in Batch Jobs

Always implement proper error handling:

#!/bin/bash

for file in ./*.md; do
  if claude -p "Process this file: $(cat "$file")" > "processed/$file" 2>&1; then
    echo "Success: $file"
  else
    echo "Failed: $file" >> errors.log
  fi
done

Review errors.log after completion to identify files requiring manual attention.

Real-World Use Cases

Batch processing with skills excels in several scenarios:

Conclusion

Claude Code skills combined with shell scripting create powerful batch processing capabilities. Start with simple single-skill workflows, then combine multiple skills for complex transformations. The key is separating iteration logic (bash) from transformation expertise (skills)—this keeps your pipelines maintainable and scalable.

Built by theluckystrike — More at zovo.one

Explore Our Developer Guides

© 2026 theluckystrike Developer Guides