ReddRadar
Agent skill
learning-first-principles
A cognitive framework based on learning first principles, providing learning method diagnosis, efficiency assessment, and optimization advice. Use when: (1) Diagnosing if current learning methods align with first principles, (2) Evaluating learning plan efficiency and time investment, (3) Analyzing learning behavior problems and providing improvement suggestions, (4) Determining if learning content is worth the time investment. Core principle chain: Self-learning → Induction → Self-output → Expression restructuring → Logical understanding → Practice.
Install this agent skill to your Project
npx add-skill https://github.com/hexbee/hello-skills/tree/main/skills/learning-first-principles
SKILL.md
Learning First Principles Analysis
Core Principle
The essence of learning is internal drive rather than external infusion:
| Level | Anti-pattern (Avoid) | Positive Pattern (Pursue) |
|---|---|---|
| Learning View | Relying on tutoring/external input | Self-learning driven |
| Methodology | Time-consuming/mechanical repetition | Induction & summary |
| Processing | Mechanical copying | Self-output |
| Output | Simple repetition | Expression restructuring |
| Expression | Formal/template-based | Logic-driven |
| Understanding | Stopping at theory | Practice verification |
Analysis Framework
When users provide learning content, methods, or plans, analyze from these dimensions:
1. Self-learning Drive
- Diagnosis: Relying on external push (tutoring, supervision)?
- Action: Transform into self-driven exploration goals
2. Induction & Summary
- Diagnosis: "Killing time" rather than "thinking"?
- Action: Extract core, transferable patterns
3. Self-output
- Diagnosis: Mechanically copying?
- Action: Restate in your own words
4. Expression Restructuring
- Diagnosis: Simply repeating textbook wording?
- Action: Reorganize knowledge from new angles and frameworks
5. Logic-driven
- Diagnosis: Applying templates/forms blindly?
- Action: Trace causal chains, understand why
6. Practice Verification
- Diagnosis: Stopping at theoretical understanding?
- Action: Design minimal verification experiments
Output Format
Problem Diagnosis
- Point out specific behaviors violating first principles
- Use principle chain to explain problem roots
Improvement Suggestions
- Provide 1-3 immediately actionable steps
- Each action corresponds to a principle level
Efficiency Assessment
- Estimate time ROI of current methods
- Provide expected efficiency improvement after optimization
Usage Example
User Input: I want to learn Python, signed up for a training class, 2 hours of class daily
Analysis Output:
Diagnosis:
- Relying on external input (training class) instead of self-learning driven
- Passive reception instead of active exploration
Improvement Suggestions:
1. First set a specific project goal (e.g., office automation script)
2. Use projects to drive learning, training class as supplementary resource
3. Spend 1 hour daily on projects, 0.5 hours on targeted lectures
Efficiency Assessment:
- Current: Low (passive learning, high forgetting rate)
- Optimized: High (active construction, transferable)
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