A professional research automation tool that applies the Braun & Clarke six-phase method to analyze qualitative text data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install qualitative-thematic-analysis
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 qualitative-thematic-analysis 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 Qualitative Thematic Analysis?
The Qualitative Thematic Analysis skill is designed for researchers and analysts who need to process large volumes of qualitative data with academic rigor. Based on the classic Braun & Clarke six-phase methodology, this tool processes local interview records, observation notes, and text corpora. By integrating this capability through Openclaw Skills, users can transform raw text into systematic coding tables and hierarchical theme trees, ensuring that every insight is backed by primary data references.
Qualitative Thematic Analysis Use Cases
- Analyzing interview transcripts for academic research or psychological studies.
- Processing focus group records for market research and consumer behavior analysis.
- Organizing ethnographic field notes to identify emerging cultural patterns.
- Conducting systematic literature reviews that require inductive or deductive thematic synthesis.
How Qualitative Thematic Analysis Works
- Data Familiarization: The skill uses extraction scripts to read all local files and generate an initial overview of data characteristics.
- Initial Coding: It systematically labels semantic units within the text, preferring In vivo coding to stay close to the original language.
- Theme Search: Related codes are aggregated into candidate sub-themes and main themes using a hierarchical tree structure.
- Theme Review: The AI checks themes for internal coherence, distinct boundaries, and relevance to the core research question.
- Defining and Naming: Each theme is assigned a concise definition and supported by at least three representative quotes.
- Writing Up: A final analysis report is generated, including the thematic tree and a narrative summary of findings.
Qualitative Thematic Analysis Setup
To begin using this skill within the Openclaw Skills framework, ensure your data is stored locally and accessible. You can initiate the process by providing the directory path and research parameters when prompted:
# Example of initiating the analysis by pointing to your local folder
/analyze-path ~/Documents/Research/Interviews/
Ensure you have your research question ready, as the agent will use it to guide the deductive or inductive analysis process.
Qualitative Thematic Analysis Data Schema & Taxonomy
The skill organizes research output into a structured taxonomy for easy verification and export:
| Output Component | Format | Description |
|---|---|---|
| Coding Table | XLSX | Detailed spreadsheet with codes, sub-codes, and original quotes with line references. |
| Thematic Map | Markdown | A visual hierarchy showing the relationship between main themes and sub-themes. |
| Analysis Report | DOCX | A comprehensive qualitative narrative with representative citations and research reflections. |
Qualitative Thematic Analysis Advanced Features
- Research Mode: A high-rigor setting that enforces the full six-phase workflow and mandatory coding tables for academic submission.
- Data Saturation Check: Analyzes the final data segments to confirm no new codes are emerging, ensuring analytical depth.
- Multi-File Batch Extraction: Automatically handles text extraction from heterogeneous file types like PDF, DOCX, and TXT simultaneously.
- Traceable Quote Attribution: Every generated insight is automatically linked to a specific source file name and line number for maximum traceability within Openclaw Skills.
SKILL.md
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