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principles-disciple

Generates principled AI behavior by capturing failures and turning them into actionable insights.

1|1|Updated Jan 22, 2026
Search Tags:#error handling#self-improvement#agent framework#ai evolution#pain driven development#ai cognition
One-click install
npx skills add https://github.com/csuzngjh/principles --skill principles-disciple
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: principles-disciple
Source: https://github.com/csuzngjh/principles/tree/main/packages/openclaw-plugin
Command: npx skills add https://github.com/csuzngjh/principles --skill principles-disciple

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires micromatch, @sinclair/typebox, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill helps you manage and evolve your AI agent's capabilities by capturing and learning from errors, fostering self-improvement through a structured "pain" feedback loop.

Core Features & Use Cases

  • Evolutionary Framework: Guides AI development through stages of learning and adaptation.
  • Pain Capture: Logs errors and failures to identify areas for improvement.
  • Principle Generation: Distills lessons learned from failures into actionable principles for future actions.
  • Use Case: When your AI agent repeatedly fails at a specific coding task, this Skill captures those failures, analyzes the root cause, and helps the agent evolve to avoid similar mistakes in the future, ultimately making it more robust and efficient.

Quick Start

Use the principles-disciple skill to initiate the evolutionary process for your agent.

Frequently Asked Questions about principles-disciple

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I implement agent self-improvement through pain-driven development?▼

Agent self-improvement through pain-driven development works by capturing errors and distilling them into actionable principles. The framework uses pain-reflection loops to manage agent cognition and ensure adaptive learning.

What is the best way to make an AI agent learn from repeated coding failures?▼

To make an AI agent learn from repeated coding failures, you use an evolutionary framework that logs errors, analyzes root causes, and generates principles to avoid similar mistakes in future actions.

How does an evolutionary agent framework manage AI cognition and error handling?▼

An evolutionary agent framework manages AI cognition by running pain-reflection loops and Evolver synergy. It captures failures as feedback to establish strategic guardrails for adaptive learning.

Can I use this evolutionary agent framework for general error handling or only for coding tasks?▼

This evolutionary agent framework can be used for general error handling. It captures any agent failures and distills them into actionable principles, making the agent robust across various tasks.

Do I need specific dependencies to run the principles-disciple agent framework?▼

You need the micromatch and @sinclair/typebox dependencies to run the principles-disciple agent framework. These libraries support the internal scripts and type validation required for the evolution process.

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