A sophisticated academic tool that utilizes four distinct AI processing modes to break cognitive inertia and generate non-trivial, innovative research topics across any discipline.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install thesis-topic-selector
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 thesis-topic-selector 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 Thesis Topic Selector?
The Thesis Topic Selector is a specialized academic engine designed to solve the problem of mediocre or repetitive research questions. By defining innovation as the disruption of default patterns, this tool employs four core AI processing modes—Direct Application, Pattern Improvement, Pattern Transfer, and Pattern Construction—to explore research spaces from multiple dimensions. It ensures that every generated topic is not just a variation of existing work, but a genuine advancement in knowledge.
Built for researchers, students, and academics, the skill operates on a foundation of structural analysis. It dismantles existing assumptions within a field and recombines them using 10 systematic innovation frameworks, such as First Principles, Reverse Thinking, and Systems Dynamics. Whether you are working in the humanities, social sciences, or STEM fields, this skill provides a rigorous pathway to discovering high-potential research directions that meet strict academic standards.
Thesis Topic Selector Use Cases
- Students looking for a unique and defensible thesis topic for undergraduate or postgraduate degrees.
- Researchers exploring new niches or cross-disciplinary angles in a saturated field.
- Academics needing to identify high-leverage intervention points in complex systems for grant proposals.
- Writers and thinkers seeking to challenge existing consensus and discover non-obvious conclusions.
How Thesis Topic Selector Works
- Field Analysis: The agent receives the target domain or research interest and adapts its persona to match the specific academic discipline (Humanities vs. STEM).
- Mode Selection: Based on the domain's characteristics, the agent selects 1 to 4 processing modes (e.g., Pattern Transfer for cross-disciplinary insights or Pattern Construction for radical new concepts).
- Creative Execution: The agent applies the selected frameworks (like Reverse Thinking or First Principles) to generate 2-5 candidate topics per mode.
- Four-Dimensional Evaluation: Each candidate is rigorously vetted against four criteria: Problem Clarity, Theoretical Tradition, Breadth/Depth Appropriateness, and Non-Triviality.
- Integration and Ranking: The agent consolidates the results, performs cross-mode analysis to identify combinable directions, and ranks them by innovation potential.
- Deepening (Optional): Once a topic is selected, the agent can generate a question tree, a preliminary outline, and locate key theoretical resources.
Thesis Topic Selector Setup
To utilize this skill within the Openclaw Skills ecosystem, ensure your AI agent has the markdown instructions loaded. You can trigger the skill using natural language commands:
# Example trigger for a specific mode
"Use Pattern Transfer to generate education research topics"
# Example for general discovery
"Help me find a thesis topic for Computer Science"
# Example for comprehensive analysis
"Use all modes to generate philosophy topics"
Thesis Topic Selector Data Schema & Taxonomy
The Thesis Topic Selector organizes its output using a structured metadata taxonomy to ensure academic rigor:
| Attribute | Description |
|---|---|
| Core Problem | The specific, debatable research question at the heart of the topic. |
| Source Mode | Identifies which of the 4 AI modes generated the idea. |
| Innovation Path | The logical derivation from a default pattern to the innovative topic. |
| 4D Assessment | A checklist of Clarity, Tradition, Scope, and Non-Triviality with status icons (✅/⚠️). |
| Theoretical Resources | Core literature or traditions the topic engages with. |
| Non-Trivial Conclusion | The predicted direction of the research that exceeds common sense. |
Thesis Topic Selector Advanced Features
- Multi-Agent Synergy: Support for chain-of-thought processing where one mode's output serves as another's input (e.g., Recursive Innovation).
- 10 Built-in Innovation Frameworks: Access to specialized logic engines including Dialectical Synthesis, Stochastic Drivers, and Gamification.
- Cross-Mode Analysis: Automatically identifies 'Combination' or 'Prerequisite' relationships between different generated topics.
- Quality Assurance Logic: Built-in validation to prevent 'hallucinated' source fields by requiring structural match and heterogeneity checks.
SKILL.md
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