Process hundreds of documents simultaneously using parallel execution, progress tracking, and resilient checkpointing logic.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install batch-processor
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install batch-processor using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Batch Processor?
The Batch Processor is a specialized automation skill designed for Openclaw Skills users who need to manage high-volume document operations. It provides a robust framework for converting, transforming, or analyzing hundreds of files concurrently by leveraging multi-core parallel processing. This tool is essential for developers and office professionals who require a scalable solution for repetitive file-based tasks without sacrificing speed or reliability.
By utilizing advanced Python patterns like process pools and checkpointing, this skill ensures that large-scale jobs are executed efficiently and can recover gracefully from interruptions. Whether you are handling complex document conversions or simple file organization, this skill streamlines the entire lifecycle of bulk data processing.
Batch Processor Use Cases
- Converting large batches of PDFs into Word documents or other editable formats.
- Extracting structured text or OCR data from entire directories of images.
- Automating file organization, renaming, and metadata updates across complex directory structures.
- Performing mass updates to document styling, including headers, footers, and templates.
How Batch Processor Works
- Scan the specified input directory for files matching the defined glob pattern.
- Initialize a process pool with a configured number of parallel workers to maximize CPU utilization.
- Distribute file processing tasks across the workers, executing specific logic like extraction or conversion.
- Monitor the execution progress in real-time using integrated tracking bars.
- Log the status of each file and save state to a checkpoint file to ensure the workflow is resume-safe.
Batch Processor Setup
To begin using this skill within your Openclaw Skills environment, install the required document processing dependencies via pip:
pip install python-docx openpyxl python-pptx reportlab jinja2
Batch Processor Data Schema & Taxonomy
| Component | Description |
|---|---|
| Input Directory | The source path containing the target files for batch processing. |
| File Pattern | Standard glob patterns (e.g., *.docx) used to filter input files. |
| Checkpoint File | A JSON-based state file that tracks processed items for resume-safe operations. |
| Results Schema | A structured list containing file paths, success status, and specific error logs for debugging. |
Batch Processor Advanced Features
- Multi-core parallel execution using ProcessPoolExecutor for significantly reduced processing time.
- Persistent state management via checkpointing to prevent redundant processing after failures.
- Real-time progress observability through tqdm integration.
- Flexible worker architecture allowing for custom processing logic for any file type.
SKILL.md
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