A rigorous analytical framework that strips away inherited assumptions to rebuild logic from foundational ground truths.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install first-principles-dv
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 first-principles-dv 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 First Principles Analysis?
First Principles Analysis is a high-performance framework designed for those who need to challenge conventional wisdom and reach the absolute truth of a situation. By leveraging the power of Openclaw Skills, this tool systematically decomposes complex topics—ranging from investment theses to product strategies—into their most basic components. It ensures that your decision-making process is based on provable facts rather than consensus, authority, or outdated historical precedents.
This skill is particularly effective when navigating high-stakes environments where being slightly wrong can be costly. By employing a ruthless stress-test on every underlying belief, Openclaw Skills allow users to identify hidden biases and survivorship failures, ultimately leading to a reconstructed model that offers a significant competitive advantage and non-obvious insights.
First Principles Analysis Use Cases
- Evaluating high-stakes strategic decisions or new business investment theses.
- Challenging product strategy assumptions when growth has plateaued.
- Analyzing career moves or industry shifts by stripping away social pressure and status-seeking.
- Debugging organizational inefficiencies that are justified by "we've always done it this way."
- Breaking down complex scientific or technical problems from scratch to find innovative solutions.
How First Principles Analysis Works
- Assumption Extraction: The skill identifies common, hidden, and authority-based assumptions embedded in the topic.
- Stress Testing: Each assumption is subjected to provability, inversion, and boundary condition audits.
- Classification: Assumptions are categorized as Survives, Conditional, or Fails based on fundamental scrutiny.
- Ground Truth Identification: The logic is reduced to atomic, falsifiable claims that remain after the debris is cleared.
- Reconstruction: A new mental model or strategy is built using only the validated ground truths.
- Decision Framework: The skill provides actionable outputs on what to start, stop, and monitor based on the rebuilt logic.
First Principles Analysis Setup
To activate this analytical framework within your environment, ensure you have the Openclaw Skills directory properly configured. You can trigger the process directly via the command line or within your AI interface.
# Trigger a first principles analysis on a specific topic
/firstprinciples "Your topic or decision here"
No additional external dependencies are required as the logic is self-contained within the skill's markdown definition.
First Principles Analysis Data Schema & Taxonomy
The First Principles Analysis skill organizes its output into a structured taxonomy to ensure clarity and logical flow.
| Phase | Component | Description |
|---|---|---|
| Phase 1 | Assumption List | A numbered list of consensus, hidden, and temporal assumptions. |
| Phase 2 | Audit Results | A status-based classification using symbols (✅, ⚠️, ❌). |
| Phase 3 | Atomic Truths | A collection of the smallest provable building blocks. |
| Phase 4 | Rebuilt Model | A comparison between conventional thinking and the new ground-truth model. |
| Phase 5 | Action Plan | A tactical framework for immediate execution and risk monitoring. |
First Principles Analysis Advanced Features
- Cross-Referencing: Every reconstruction step points back to specific numbered assumptions for full auditability.
- Contrarian Calibration: Specifically tuned to generate at least one non-obvious or uncomfortable insight to avoid confirmation bias.
- Epistemic Humility: Includes built-in risk monitoring to identify when the rebuilt model itself might require invalidation.
- Multi-Domain Adaptability: Functions across technical, financial, and personal development domains using the same Openclaw Skills logic.
SKILL.md
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