A comprehensive AI-driven framework designed to manage the full lifecycle of academic dissertation writing, from data synthesis to theoretical analysis.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install dissertation-workflow-core
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 dissertation-workflow-core 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 Dissertation Workflow System Core (DWS-Core)?
The Dissertation Workflow System Core (DWS-Core) is a high-level orchestration skill for Openclaw Skills that transforms an AI agent into a virtual research team. Specifically tailored for the Sociology of Education, it manages five distinct agent roles to ensure academic rigor, theoretical consistency with Giddens' Structuration Theory, and seamless integration of qualitative interview data into formal chapters. It serves as a centralized hub for managing knowledge bases, mentor feedback, and complex writing workflows.
By utilizing this skill within Openclaw Skills, researchers can maintain absolute logical consistency across hundreds of pages. The system enforces an evidence-first approach, where theoretical claims must be grounded in empirical data, while simultaneously handling technical tasks like Zotero citation management and multi-language translation for academic English standards.
Dissertation Workflow System Core (DWS-Core) Use Cases
- Drafting new dissertation sections grounded in qualitative interview evidence.
- Polishing existing drafts to meet high-level academic registers and mentor standards.
- Translating Chinese academic field notes and texts into professional English.
- Auditing completed chapters for research question alignment and theoretical depth.
- Managing complex Zotero libraries and academic citations automatically.
How Dissertation Workflow System Core (DWS-Core) Works
- The system analyzes user input to determine one of five working modes: Generate, Edit, Translate, Review, or Theory.
- It triggers a Python-based status tracker to identify the current chapter, completion percentage, and active tasks.
- It loads mandatory reference files including the Research Question framework and previous chapters to serve as logical constraints.
- It queries integrated knowledge bases, such as Google Drive interview transcripts and Zotero libraries, to synthesize evidence.
- The lead agent role (e.g., Senior Sociologist or Writing Specialist) generates the output following strict academic style guides.
- An internal reviewer role performs a final quality control check against a multi-point checklist before delivery.
Dissertation Workflow System Core (DWS-Core) Setup
To deploy this skill within your Openclaw Skills environment, follow these steps:
# Navigate to your skills directory
cd /home/ubuntu/skills/
# Clone the dissertation-workflow-system-core repository
git clone [repository-link]
# Initialize the status tracker for your project
python3 ./dissertation-workflow-system-core/scripts/status_tracker.py --init
# Configure your Zotero API credentials in the connector script
nano ./dissertation-workflow-system-core/scripts/zotero_connector.py
Dissertation Workflow System Core (DWS-Core) Data Schema & Taxonomy
This skill organizes dissertation data through a multi-layer taxonomy to ensure context retention across the Openclaw Skills workflow:
| Data Layer | Storage Location | Function |
|---|---|---|
| Constraints | /01_Completed_Chapters/ |
Immutable references for consistency |
| Evidence | /03_Interview_Data/ |
Source material for empirical claims |
| Logic | /references/rq_framework.md |
Core RQs and theoretical boundaries |
| Standards | /references/mentor_patterns.md |
Stylistic and academic quality benchmarks |
| Automation | /scripts/ |
Python hooks for Zotero and status tracking |
Dissertation Workflow System Core (DWS-Core) Advanced Features
- Multi-Agent Team Orchestration: Automatically rotates lead roles between Methodologists, Sociologists, and Writing Specialists based on the task.
- Dynamic Zotero Integration: Uses Python hooks to search, add, and cite literature directly from the command line.
- Interactive UI Templates: Employs structured selection interfaces to clarify user intent and update project status without open-ended prompts.
- Theory-Data Grounding: Enforces a strict validation rule requiring 2-4 interview excerpts for every theoretical argument generated.
- Automated Quality Control: Simulates a dissertation committee review to flag logical leaps or terminology inconsistencies.
SKILL.md
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