An automated retrieval-augmented generation tool that extracts text from various document formats to answer user queries.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install document-qa
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 document-qa 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 Document Q&A?
The Document Q&A skill is a specialized utility designed to bridge the gap between static file storage and active AI intelligence. By processing formats like PDF, Microsoft Word, Excel, and plain text, it provides a seamless way for developers to query their local data. This skill is a vital addition to the library of Openclaw Skills, enabling agents to ingest large volumes of text and provide context-aware answers without manual copy-pasting.
Whether you are dealing with a single report or an entire directory of project documentation, this skill automates the extraction and synthesis of information. It utilizes specialized readers for different file types to ensure high-fidelity text retrieval, making it an essential tool for automated research and technical analysis within the Openclaw Skills ecosystem.
Document Q&A Use Cases
- Analyzing technical research papers in PDF format to find specific methodology details.
- Summarizing project objectives and milestones from a directory of DOCX files.
- Querying unstructured TXT logs or notes to identify recurring patterns or issues.
- Extracting specific financial metrics or data points from Excel spreadsheets.
How Document Q&A Works
- The user initiates the skill by providing a local file path or folder path along with a natural language question.
- The system identifies the file extensions present and selects the appropriate parsing logic for each file.
- Text extraction is performed using internal scripts or dependent Openclaw Skills like the iyeque-pdf-reader.
- All extracted content is compiled into a context buffer which is then analyzed by the AI agent.
- The agent generates a comprehensive answer based strictly on the content found within the provided documents.
Document Q&A Setup
To get started with this skill, ensure your environment is prepared with the necessary dependencies:
# Install Excel processing libraries
pip install pandas openpyxl
# Ensure the PDF reader skill is available in your workspace
# This is required for .pdf support
Run the skill via the command line using the following syntax:
python ~/.openclaw/workspace/skills/document-qa/scripts/run_qa.py "<path_to_file_or_folder>" "<Your question>"
Document Q&A Data Schema & Taxonomy
The skill processes input through a structured workflow to ensure data integrity during context extraction:
| Feature | Specification |
|---|---|
| Supported Extensions | .pdf, .docx, .txt, .xlsx |
| Input Source | Local absolute file path or directory path |
| Context Handling | Aggregate text extraction from all supported files in a target directory |
| Dependencies | iyeque-pdf-reader-1.1.0 (for PDFs), pandas (for Excel) |
Document Q&A Advanced Features
- Recursive directory scanning to ingest context from multiple files simultaneously.
- Native integration with other Openclaw Skills to extend document processing capabilities.
- Support for tabular data extraction from Excel workbooks.
- Modular script design allowing for custom prompt engineering or specific extraction logic.
SKILL.md
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