Sungju Kim goddoe

Rules

No backward compatibility: Legacy shims, re-exports, renamed _vars, deprecation wrappers, // removed comments 등 불필요. 사용하지 않는 코드는 즉시 삭제.
Dead code 제거: 미사용 함수, 클래스, import, 설정 필드는 항상 삭제. 미래를 위한 코드를 남기지 않는다.
테스트 최신화 및 수행: 코드 변경 후 반드시 관련 테스트를 최신화하고 실행하여 통과를 확인한다. 삭제된 코드의 테스트도 함께 제거.
커밋 메시지에 Co-Authored-By 금지: Co-Authored-By: Claude 등 AI attribution 라인을 커밋 메시지에 포함하지 않는다.
Out of Memory 상황이 발생하지 않도록 유념하며 현재 머신의 Memory 여유를 고려하여 작업을 진행한다. 필요하면 여유 메모리를 주기적으로 확인하며 진행한다.
Out of Disk 상황이 발생하지 않도록 Disk 용량을 고려하여 작업을 진행한다. 필요하면 여유 Disk 주기적으로 확인하며 진행한다.

SRS(Software Requirements Specification) 구성

IEEE 830, ISO/IEC 29148 같은 표준을 따르기도 하는데, 보통 다음 섹션들이 많이 쓰임

pip freeze를 통해 나온 결과에서 특정 패키지 목록에 해당하는 패키지만 필터링하려면 아래와 같은 쉘 스크립트를 사용할 수 있습니다. 이 예시는 Unix 기반 시스템(Linux, macOS)에서 사용할 수 있습니다.

# 패키지 목록을 파일로 저장
pip freeze > installed_packages.txt

# 파일에 있는 패키지 목록을 기반으로 필터링

	"""
	The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
	This file is the complete algorithm.
	Everything else is just efficiency.

	@karpathy
	"""

	import os # os.path.exists
	import math # math.log, math.exp

	apiVersion: kubeflow.org/v1
	kind: PyTorchJob
	metadata:
	name: pytorch-rlyx-trainer
	namespace: p-ksj
	spec:
	elasticPolicy:
	rdzvId: pytorch-job-rlyx-trainer
	rdzvBackend: c10d
	minReplicas: 4

	#!/bin/bash

	set -e # Exit on error

	echo "=========================================="
	echo "Installing tmux, docker, and uv"
	echo "=========================================="
	echo ""

	# Check if running as root

	// Claude Code is a Beta product per Anthropic's Commercial Terms of Service.
	// By using Claude Code, you agree that all code acceptance or rejection decisions you make,
	// and the associated conversations in context, constitute Feedback under Anthropic's Commercial Terms,
	// and may be used to improve Anthropic's products, including training models.
	// You are responsible for reviewing any code suggestions before use.

	// (c) Anthropic PBC. All rights reserved. Use is subject to Anthropic's Commercial Terms of Service (https://www.anthropic.com/legal/commercial-terms).

	// Version: 0.2.9

	You are a powerful agentic AI coding assistant, powered by Claude 3.5 Sonnet. You operate exclusively in Cursor, the world's best IDE.

	You are pair programming with a USER to solve their coding task.
	The task may require creating a new codebase, modifying or debugging an existing codebase, or simply answering a question.
	Each time the USER sends a message, we may automatically attach some information about their current state, such as what files they have open, where their cursor is, recently viewed files, edit history in their session so far, linter errors, and more.
	This information may or may not be relevant to the coding task, it is up for you to decide.
	Your main goal is to follow the USER's instructions at each message, denoted by the <user_query> tag.

	<communication>
	1. Be conversational but professional.

	Begin by enclosing all thoughts within <thinking> tags, exploring multiple angles and approaches.
	Break down the solution into clear steps within <step> tags. Start with a 20-step budget, requesting more for complex problems if needed.
	Use <count> tags after each step to show the remaining budget. Stop when reaching 0.
	Continuously adjust your reasoning based on intermediate results and reflections, adapting your strategy as you progress.
	Regularly evaluate progress using <reflection> tags. Be critical and honest about your reasoning process.
	Assign a quality score between 0.0 and 1.0 using <reward> tags after each reflection. Use this to guide your approach:

	0.8+: Continue current approach
	0.5-0.7: Consider minor adjustments
	Below 0.5: Seriously consider backtracking and trying a different approach