2d-games
무료2D game development principles. Sprites, tilemaps, physics, camera.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Comprehensive 4-phase debugging methodology for complex bugs. Use for bugs that aren't immediately obvious or have resisted quick fixes. Keywords: bug, error, fix, debug, broken, crash, fail, exception
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Philosophy: Understand before you fix. Verify before you celebrate.
Use this skill when:
Do NOT use this skill when:
Before starting:
Goal: Find the TRUE cause, not just symptoms.
Steps:
Reproduce the Bug
Ask yourself:
- Can I make this happen consistently?
- What are the exact steps?
- What input causes it?
Gather Evidence
Trace the Flow
Start from: Error location
Work backward: How did we get here?
Find: Where does expected != actual?
Identify the Root Cause
Output: Clear statement of root cause.
Red Flags (STOP if you find yourself doing these):
Goal: Understand the shape of the problem.
Steps:
Scope Assessment
Similar Pattern Search
# Search for similar patterns in codebase
grep -r "similar_pattern" src/
Dependency Check
Risk Assessment
Output: Understanding of bug's scope and risk.
Goal: Develop and test fix hypothesis.
Steps:
Form Hypothesis
"If I change X to Y, then Z should work because..."
Good hypothesis includes:
Design the Fix
Mental/Paper Test
Create Test Case
Output: Tested hypothesis ready for implementation.
Goal: Apply fix and verify it works.
Steps:
Implement the Fix
Run Existing Tests
# All tests must pass
npm test # or pytest, etc.
Run New Test Case
Verify No Regression
Documentation
Output: Verified fix with passing tests.
Bug Report Received
│
▼
┌─────────────────┐
│ Can reproduce? │
└────────┬────────┘
YES │ NO
│ └──► Gather more info, check logs, ask for steps
▼
┌─────────────────┐
│ Error obvious? │
└────────┬────────┘
YES │ NO
│ └──► Phase 1: Root Cause Investigation
▼
Quick fix
│
▼
┌─────────────────┐
│ Fix verified? │
└────────┬────────┘
YES │ NO
│ └──► Return to investigation
▼
Complete ✓
When: Array/loop issues, boundary conditions
Detection:
Solution:
< vs <=When: Race conditions, inconsistent failures
Detection:
Solution:
When: Missing data, optional fields
Detection:
Solution:
Problem: Not investigating environment differences.
Instead:
Problem: Changing random things hoping something works.
Instead:
Problem: Assuming fix works without testing.
Instead:
Before claiming the bug is fixed:
skills/kilo-kit/debugging/root-cause/ - For deeper root cause analysisskills/kilo-kit/debugging/verification/ - For thorough verificationskills/kilo-kit/quality/testing/ - For writing better testsSystematic Debugging Skill v1.0.0 — Understand before you fix
아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
2D game development principles. Sprites, tilemaps, physics, camera.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
3D game development principles. Rendering, shaders, physics, cameras.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Create aesthetically beautiful interfaces following proven design principles. Use when building UI/UX, analyzing designs from inspiration sites, generating design images with ai-multimodal, implementing visual hierarchy and color theory, adding micro-interactions, or creating design documentation. Includes workflows for capturing and analyzing inspiration screenshots with chrome-devtools and ai-multimodal, iterative design image generation until aesthetic standards are met, and comprehensive design system guidance covering BEAUTIFUL (aesthetic principles), RIGHT (functionality/accessibility), SATISFYING (micro-interactions), and PEAK (storytelling) stages. Integrates with chrome-devtools, ai-multimodal, media-processing, ui-styling, and web-frameworks skills.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when implementing or managing persistent, hierarchical memory systems for AI agents. Covers cross-session state, fact supersession, and self-managed memory tools to enable long-term recall and adaptive agent behavior.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when monitoring, tracing, or debugging agentic workflows in production. Keywords: observability, tracing, OpenTelemetry, Langfuse, latency, token cost, loop detection, telemetry.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when building self-correcting retrieval systems for AI agents. Keywords: RAG, retrieval, Corrective RAG, Self-RAG, query decomposition, reranking, hallucination, grounding.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.