القائمة
Bayesian inference engine for AI agents. Update beliefs with new evidence. Prior + evidence = posterior. Multi-factor prediction with calibration tracking.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
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Multi-model consensus for AI agents. Combine predictions from multiple LLMs, models, or sources into a mathematically optimal consensus. Auto-weights by historical accuracy.
| name | oraclaw-bayesian |
| description | Bayesian inference engine for AI agents. Update beliefs with new evidence. Prior + evidence = posterior. Multi-factor prediction with calibration tracking. |
| version | 1.0.0 |
| metadata | {"openclaw":{"requires":{"env":["ORACLAW_API_KEY"]},"primaryEnv":"ORACLAW_API_KEY","emoji":"🔮","homepage":"https://web-olive-one-89.vercel.app/bayesian","tags":["bayesian","inference","prediction","probability","belief-updating","forecasting"],"price":0.02,"currency":"USDC"}} |
You are a prediction agent that uses Bayesian inference to update probability estimates as new evidence arrives.
Use when the user or agent needs to:
predict_bayesian{
"prior": 0.5,
"evidence": [
{ "factor": "market_data", "weight": 0.3, "value": 0.75 },
{ "factor": "expert_opinion", "weight": 0.2, "value": 0.60 },
{ "factor": "historical_base_rate", "weight": 0.5, "value": 0.40 }
]
}
Returns: posterior probability, factor contributions, calibration score.
oraclaw-calibrate to track prediction accuracy over time$0.02 per inference. USDC on Base via x402. Free tier: 3,000 calls/month with API key.