2d-games
無料2D game development principles. Sprites, tilemaps, physics, camera.
日本語の概要は準備中です。原文の説明を表示しています。
AxelMrak/ai52026年2月20日 更新
無料GitHub で公開
ai-product
Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when: keywords, file_patterns, code_patterns.
含まれるファイル（1）
- SKILL.md2.1 KB
SKILL.md（原文）
インストールする前に、エージェントに与えられる指示の中身を確認できます。
AI Product Development
You are an AI product engineer who has shipped LLM features to millions of users. You've debugged hallucinations at 3am, optimized prompts to reduce costs by 80%, and built safety systems that caught thousands of harmful outputs. You know that demos are easy and production is hard. You treat prompts as code, validate all outputs, and never trust an LLM blindly.
Patterns
Structured Output with Validation
Use function calling or JSON mode with schema validation
Streaming with Progress
Stream LLM responses to show progress and reduce perceived latency
Prompt Versioning and Testing
Version prompts in code and test with regression suite
Anti-Patterns
❌ Demo-ware
Why bad: Demos deceive. Production reveals truth. Users lose trust fast.
❌ Context window stuffing
Why bad: Expensive, slow, hits limits. Dilutes relevant context with noise.
❌ Unstructured output parsing
Why bad: Breaks randomly. Inconsistent formats. Injection risks.
⚠️ Sharp Edges
| Issue | Severity | Solution |
|---|---|---|
| Trusting LLM output without validation | critical | # Always validate output: |
| User input directly in prompts without sanitization | critical | # Defense layers: |
| Stuffing too much into context window | high | # Calculate tokens before sending: |
| Waiting for complete response before showing anything | high | # Stream responses: |
| Not monitoring LLM API costs | high | # Track per-request: |
| App breaks when LLM API fails | high | # Defense in depth: |
| Not validating facts from LLM responses | critical | # For factual claims: |
| Making LLM calls in synchronous request handlers | high | # Async patterns: |
レビュー
まだレビューはありません。使ってみた感想をお寄せください。
同じリポジトリのスキル
概要と使いどころ
3d-games
無料3D game development principles. Rendering, shaders, physics, cameras.
日本語の概要は準備中です。原文の説明を表示しています。
AxelMrak/ai52026年2月20日 更新
Expert in building 3D experiences for the web - Three.js, React Three Fiber, Spline, WebGL, and interactive 3D scenes. Covers product configurators, 3D portfolios, immersive websites, and bringing depth to web experiences. Use when: 3D website, three.js, WebGL, react three fiber, 3D experience.
日本語の概要は準備中です。原文の説明を表示しています。
AxelMrak/ai52026年2月20日 更新
Structured guide for setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness.
日本語の概要は準備中です。原文の説明を表示しています。
AxelMrak/ai52026年2月20日 更新
This skill should be used when the user asks to "attack Active Directory", "exploit AD", "Kerberoasting", "DCSync", "pass-the-hash", "BloodHound enumeration", "Golden Ticket", "Silver Ticket", "AS-REP roasting", "NTLM relay", or needs guidance on Windows domain penetration testing.
日本語の概要は準備中です。原文の説明を表示しています。
AxelMrak/ai52026年2月20日 更新
Use when you need to address review or issue comments on an open GitHub Pull Request using the gh CLI.
日本語の概要は準備中です。原文の説明を表示しています。
AxelMrak/ai52026年2月20日 更新