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token-budget

Agent basina token kullanimi takibi, maliyet optimizasyonu, butce limitleri ve ROI analizi. Session ve proje bazinda harcama raporlari. Hangi agent ne kadar token tuketiyor, hangisi verimli, hangisi israf.

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包含的文件(1)

  • SKILL.md5.9 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Token Budget Management

Her agent cagri token harcar. Butce yonetimi olmadan maliyetler kontrolsuz buyur.

Maliyet Tablosu (2026 Q2)

ModelInput (1M token)Output (1M token)Cache Read (1M)
Opus 4.6$15.00$75.00$1.50
Sonnet 4.6$3.00$15.00$0.30
Haiku 4.5$0.80$4.00$0.08

Agent Basina Ortalama Maliyet

Agent TipiOrtalama Token/CagriOrtalama MaliyetNotlar
scout (arastirma)15K-50K$0.15-0.75Cok dosya okur
code-reviewer10K-30K$0.10-0.45Diff boyutuna bagli
architect20K-60K$0.30-0.90Derin dusunme gerektirir
spark (quick fix)3K-10K$0.03-0.15En verimli
kraken (TDD)30K-100K$0.45-1.50Test + implement
sleuth (debug)20K-80K$0.30-1.20Bug karmasikligina bagli
verifier5K-15K$0.05-0.22Build + test calistirma
security-reviewer10K-40K$0.15-0.60Tarama derinligine bagli
planner15K-40K$0.22-0.60Plan buyuklugune bagli

Butce Planlama

Session Butcesi

KUCUK IS (bug fix, kucuk feature):
  Beklenen: 50K-150K token
  Butce: $0.50-2.00
  Agent sayisi: 2-4

ORTA IS (feature, refactoring):
  Beklenen: 200K-500K token
  Butce: $3.00-7.00
  Agent sayisi: 4-8

BUYUK IS (yeni modul, buyuk refactor):
  Beklenen: 500K-2M token
  Butce: $7.00-30.00
  Agent sayisi: 8-15

SWARM (tam ekip):
  Beklenen: 1M-5M token
  Butce: $15.00-75.00
  Agent sayisi: 15-30

Aylik Butce Tahmini

Gunluk 3-5 session x 30 gun:

Hafif kullanim (vibe coding):
  ~100K token/gun = $1.50/gun = ~$45/ay

Normal kullanim (aktif gelistirme):
  ~500K token/gun = $7.50/gun = ~$225/ay

Yogun kullanim (tam ekip, swarm):
  ~2M token/gun = $30/gun = ~$900/ay

Claude Max abone ise:
  Sabit $200/ay -- token limiti var ama birim maliyet yok
  ROI: Normal kullanim ustu her sey Max ile karli

Maliyet Optimizasyon Stratejileri

1. Model Routing (En Buyuk Tasarruf)

Opus kullan:
  - Mimari kararlar (architect)
  - Karmasik debug (sleuth)
  - Guvenlik analizi (security-reviewer)
  - Kritik code review

Sonnet kullan:
  - Genel gelistirme (kraken, spark)
  - Rutin review (code-reviewer)
  - Dokumantasyon (technical-writer)
  - Test yazma (tdd-guide)

Sonuc: %40-60 maliyet dususu, %5-10 kalite kaybı

2. Context Yonetimi

YAPMA: 5 dosyayi tamamen okuyup agent'a gonder
YAP:   Sadece ilgili fonksiyonlari gonder

YAPMA: Her seferinde tum CLAUDE.md'yi inject et
YAP:   Sadece ilgili kurallari sec

YAPMA: Agent'a "her seyi kontrol et" de
YAP:   Spesifik kontrol listesi ver

Token tasarrufu: %30-50

3. Agent Secimi

PAHALI YOLDAN GITME:
  architect (60K) + kraken (100K) + verifier (15K) = 175K token

VERIMLI YOL:
  spark (10K) + verifier (10K) = 20K token
  (Kucuk is icin spark yeterli, architect/kraken gereksiz)

Kural: Is buyuklugune uygun agent sec

4. Cache Kullanimi

Ayni dosyayi tekrar tekrar okuma:
  Ilk okuma: 10K token (tam fiyat)
  Cache hit: 10K token (%90 indirimli)

Strateji: Session basinda ilgili dosyalari bir kere oku,
sonraki agent'lar cache'ten okusun

5. Paralel vs Sequential

PARALEL (daha pahali ama hizli):
  3 agent ayni anda = 3x token ama 3x hizli
  Kullan: Deadline varsa, bagimsiz isler

SEQUENTIAL (daha ucuz):
  Agent 1 bitir → ciktisini Agent 2'ye ver
  Kullan: Butce kisitliysa, bagimli isler

ROI Analizi

Agent Basina ROI

ROI = (Tasarruf edilen sure x saat ucreti) / Agent maliyeti

Ornek: code-reviewer
  Maliyet: ~$0.30/review
  Tasarruf: ~15 dk/review (manual review vs)
  Saat ucreti: $50/saat
  ROI: ($12.50) / ($0.30) = 41x

Ornek: sleuth (bug investigation)
  Maliyet: ~$0.75/investigation
  Tasarruf: ~45 dk/bug (manual debug vs)
  ROI: ($37.50) / ($0.75) = 50x

Ornek: architect (buyuk plan)
  Maliyet: ~$0.90/plan
  Tasarruf: ~2 saat (manual planning vs)
  ROI: ($100) / ($0.90) = 111x

En Yuksek ROI Agent'lar

SiralamaAgentROINeden
1architect111xBuyuk zaman tasarrufu, dusuk maliyet
2sleuth50xBug investigation cok zaman alir
3code-reviewer41xHer commit icin gerekli
4verifier35xOtomatik quality gate
5spark30xKucuk isler icin cok verimli

En Dusuk ROI Agent'lar

AgentROINedenOneri
scout (gereksiz arama)5xBazen cok dosya okur, az bilgi bulurSpesifik soru sor
kraken (kucuk is)8xTDD overhead kucuk isler icin fazlaKucuk is = spark
designer (sadece oneri)3xOneri verir ama implement etmezFrontend-dev yeterli

Harcama Raporu Sablonu

# Token Harcama Raporu - [Tarih]

## Ozet
- Toplam token: XXX,XXX
- Tahmini maliyet: $XX.XX
- Agent sayisi: X
- Session suresi: X saat

## Agent Bazli Dagilim

| Agent | Token | Maliyet | Is | ROI |
|-------|------:|--------:|---|----|
| architect | 45K | $0.67 | Auth redesign plani | 111x |
| kraken | 85K | $1.27 | Implementation | 25x |
| code-reviewer | 20K | $0.30 | Review | 41x |
| verifier | 12K | $0.18 | Final check | 35x |
| **TOPLAM** | **162K** | **$2.42** | | |

## Optimizasyon Onerisi
- kraken yerine spark kullanilabilirdi (-70K token)
- architect ciktisi daha spesifik olabilirdi (-15K token)
- Potansiyel tasarruf: %52

vibecosystem Entegrasyonu

  • cost-tracker agent: Bu skill'i kullanarak session maliyet raporu uretir
  • smart-model-routing skill: Model secimini maliyet/kalite dengesine gore yapar
  • swarm-optimizer agent: Swarm calistirmalarinda butce optimizasyonu yapar
  • session-replay-analyzer agent: Gecmis session'larin token verimliligini analiz eder

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