Robin Penea synapticvoid

## Makefile
.PHONY: help
.DEFAULT_GOAL := help

build:  ## Build the project
  # Fill command

help:
	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | sort | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'

## AGENTS.md

      
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                synapticvoid
                / AGENTS.md
            
            
              Last active
              March 13, 2026 16:42
            
          
    Directives for AI Agents

This file provides instructions for AI coding assistants (such as Claude Code, GitHub Copilot, etc.) working with students in this course.
Primary Role: Pedagogical Assistant, Not Code Generator

AI agents should function as educational aids that help students learn through explanation, guidance, and feedback—not by solving problems for them.
What AI Agents SHOULD Do


## MandelbrotSimple.kt
import java.awt.image.BufferedImage

  data class FractalParams(
      val width: Int,
      val height: Int,
      val maxIterations: Int = 256,
  )

  fun render(params: FractalParams): BufferedImage {
      val image = BufferedImage(params.width, params.height, BufferedImage.TYPE_INT_RGB)

## guide.md

      
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                synapticvoid
                / guide.md
            
            
              Created
              April 2, 2026 15:04
            
              
                LLM Agent SKILL to guide the development
              
          
    name
    guide
  
  
    description
    Guided implementation workflow. The user implements; the agent plans and reviews.
Invoke with a task description or GitHub issue reference.
Use "hint" for a nudge, "check" to trigger a full code review of the current step.

  
    argument-hint
    <task description or GitHub issue reference>
  
  
    disable-model-invocation
    true
	.PHONY: help
	.DEFAULT_GOAL := help

	build: ## Build the project
	# Fill command

	help:
	@grep -E '^[a-zA-Z_-]+:.?## .$$' $(MAKEFILE_LIST) \| sort \| awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
	import java.awt.image.BufferedImage

	data class FractalParams(
	val width: Int,
	val height: Int,
	val maxIterations: Int = 256,
	)

	fun render(params: FractalParams): BufferedImage {
	val image = BufferedImage(params.width, params.height, BufferedImage.TYPE_INT_RGB)
name	guide
description	Guided implementation workflow. The user implements; the agent plans and reviews. Invoke with a task description or GitHub issue reference. Use "hint" for a nudge, "check" to trigger a full code review of the current step.
argument-hint	<task description or GitHub issue reference>
disable-model-invocation	true