vuralserhat86/skills/prompt_optimizer
skills/prompt_optimizer/SKILL.md
--- name: prompt_optimizer router_kit: AIKit description: Mevcut promptların token kullanımını ve başarı oranını optimize etme. metadata: skillport: category: ai tags: [agents, algorithms, artificial intelligence, automation, chatbots, cognitive services, deep learning, embeddings, frameworks, generative ai, inference, large language models, llm, machine learning, model fine-tuning, natural language processing, neural networks, nlp, openai, prompt engineering, prompt optimizer, rag, re
$ install --global
skillsauthnpx skillsauth add vuralserhat86/antigravity-agentic-skills skills/prompt_optimizerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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TrivyContainer and dependency vulnerability scanner
95%
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95%
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95%
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Snyk (dep)Open source security scanning
50%
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50%
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OWASP Dep-Check
50%
Last scanned: Apr 22, 2026, 6:01 AM126.5s1 file scanned
SKILL.md
- name:
- prompt_optimizer
- router_kit:
- AIKit
- description:
- Mevcut promptların token kullanımını ve başarı oranını optimize etme.
- category:
- ai
- tags:
- [agents, algorithms, artificial intelligence, automation, chatbots, cognitive services, deep learning, embeddings, frameworks, generative ai, inference, large language models, llm, machine learning, model fine-tuning, natural language processing, neural networks, nlp, openai, prompt engineering, prompt optimizer, rag, retrieval augmented generation, tools, vector databases, workflow automation] - prompt-refinement
⚡ Prompt Optimizer
Prompt verimliliğini artırma ve token maliyeti düşürme metodolojisi.
Prompt Optimizer v1.1 - Enhanced
🔄 Workflow
Kaynak: Anthropic - Prompt Engineering Best Practices
Aşama 1: Analysis & Benchmarking
- [ ] Analyze: Mevcut promptun nerede hata yaptığını veya neden çok token harcadığını belirle.
- [ ] Baseline: Başarı oranını ve ortalama token sayısını kaydet.
Aşama 2: Rewriting & Compression
- [ ] Clarity: Gereksiz yan cümleleri at, net emir kipleri kullan.
- [ ] Compression: Anlam kaybı olmadan token sayısını azalt (Stopwords temizliği vb.).
- [ ] Prompt Chaining: Tek bir dev prompt yerine görevleri küçük, zincirleme promptlara böl.
Aşama 3: Verification (A/B Test)
- [ ] Test: Optimize edilmiş promptu eskisiyle aynı inputlar üzerinde kıyasla.
- [ ] Score: Yanıt doğruluğu, hızı ve maliyeti üzerinden puanla.
Kontrol Noktaları
| Aşama | Doğrulama | |-------|-----------| | 1 | Token tasarrufu >%20 sağlandı mı? | | 2 | Başarı oranı (Accuracy) düştü mü? | | 3 | Modelin çıktı formatı tutarlı kalmaya devam ediyor mu? |
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