home / skills / hexbee / hello-skills / learning-first-principles
This skill analyzes learning strategies against first principles to diagnose flaws, optimize plans, and boost efficient, self-driven learning.
npx playbooks add skill hexbee/hello-skills --skill learning-first-principlesReview the files below or copy the command above to add this skill to your agents.
---
name: "learning-first-principles"
description: "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."
---
# 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)
```
This skill implements a learning-first-principles cognitive framework that diagnoses learning methods, assesses efficiency, and provides concrete optimization advice. It maps user learning behaviors to a core principle chain (Self-learning → Induction → Self-output → Expression restructuring → Logical understanding → Practice) and produces actionable steps to improve learning ROI. Use it to decide whether a plan or content is worth your time and how to make learning more self-driven and effective.
Given a description of learning goals, methods, schedules, or materials, the skill inspects six dimensions: self-learning drive, induction and summary, self-output, expression restructuring, logical reasoning, and practice verification. It flags anti-patterns, links them to the principle chain, estimates current time-ROI, and suggests 1–3 prioritized actions tied to specific principles. The output includes a concise diagnosis, concrete improvement steps, and an expected efficiency shift after optimization.
How many immediate actions will I get?
You will receive 1–3 prioritized, principle-linked actions that are simple to implement.
Can this assess time ROI quantitatively?
It provides an estimated ROI band (low/medium/high) and expected improvement after applying optimizations, not exact minute-by-minute metrics.