reputation-patterns

Agent Building

Agent reputation scoring, performance tier system, trust calibration, and task affinity matching

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Source SKILL.md: https://github.com/vibeeval/vibecosystem/blob/HEAD/skills/reputation-patterns/SKILL.md

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Reputation Patterns

Agent Reputation Score (ARS)

interface AgentReputation {
  agentId: string
  score: number           // 0-100
  tier: 'S' | 'A' | 'B' | 'C' | 'D'
  totalTasks: number
  successRate: number     // 0-1
  firstPassRate: number   // QA'den ilk seferde geçme oranı
  avgRetries: number
  specialties: string[]   // Başarılı olduğu task tipleri
  weaknesses: string[]    // Başarısız olduğu task tipleri
}

// Score hesaplama
function calculateARS(agent: AgentReputation): number {
  const weights = {
    successRate: 0.35,
    firstPassRate: 0.25,
    consistency: 0.20,    // son 10 task varyansı
    efficiency: 0.20      // ortalama retry sayısı
  }

  return (
    agent.successRate * weights.successRate * 100 +
    agent.firstPassRate * weights.firstPassRate * 100 +
    (1 - agent.avgRetries / 3) * weights.consistency * 100 +
    (agent.totalTasks > 5 ? 1 : 0.5) * weights.efficiency * 100
  )
}

Tier System

Tier	ARS Range	Yetki	Açıklama
S	90-100	Otonom	Her task'ı alabilir, QA skip
A	75-89	Güvenilir	Çoğu task, standart QA
B	60-74	Normal	Standart task, tam QA
C	40-59	İzlemede	Basit task, sıkı QA
D	0-39	Kısıtlı	Cross-training gerekli

Decay & Recovery

Decay:
- 7 gün inaktif → -2 puan
- 14 gün inaktif → -5 puan
- QA FAIL → -5 puan (severity'ye göre)
- Escalation → -10 puan

Recovery:
- QA PASS (first try) → +3 puan
- QA PASS (retry) → +1 puan
- Complex task başarı → +5 puan
- Cross-training başarı → +2 puan

Task-Type Affinity

## Agent Affinity Matrix

| Agent | Frontend | Backend | DB | Security | Score |
|-------|----------|---------|----|---------|----|
| spark | 85 | 70 | 50 | 40 | B |
| kraken | 60 | 90 | 80 | 65 | A |
| frontend-dev | 95 | 30 | 20 | 30 | S(FE) |
| backend-dev | 20 | 92 | 75 | 60 | S(BE) |

Task assignment: Highest affinity agent with available capacity

Reliability Prediction

def predict_success(agent_id: str, task_type: str) -> float:
    """Agent'ın belirli task tipinde başarı olasılığı"""
    agent = get_agent(agent_id)
    base_rate = agent.success_rate
    type_affinity = agent.affinity.get(task_type, 0.5)
    recent_trend = agent.last_5_tasks_success_rate

    return (base_rate * 0.4 + type_affinity * 0.35 + recent_trend * 0.25)

Canavar Integration

# Skill matrix'ten data çek
cat ~/.claude/canavar/skill-matrix.json | jq '.agents[] | {name, score, tier}'

# Error ledger'dan failure pattern
cat ~/.claude/canavar/error-ledger.jsonl | jq 'select(.agent == "spark")'

# Leaderboard
node ~/.claude/hooks/dist/canavar-cli.mjs leaderboard

Checklist

Her agent'ın ARS score'u tracked
Tier assignment otomatik
Decay/recovery mekanizması aktif
Task-type affinity matrisi var
Reliability prediction kullanılıyor
Cross-training plan (D-tier agent'lar için)
Canavar error-ledger entegre

Anti-Patterns

Tüm agent'lara eşit güvenme (reputation'a bak)
Low-tier agent'a kritik task verme
Score'u sadece success/fail'e dayandırma (context önemli)
Recovery yolu olmayan punishment