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Oraclaw Decide

为 AI Agent 提供决策智能:从备选项中选出期望价值最高者、按情境调整决策、用 PageRank 分析决策依赖图并定位瓶颈与关键路径、对多来源预测做收敛度评分并识别离群值。分析由远程工具执行,需配置 ORACLAW_API_KEY,超出免费额度后按次计费。

whatsonyourmind
whatsonyourmind
热度 36.79
最近更新 2026-05-11 17:37:19
分类:数据依赖:第三方 API应用场景:推荐 / 报告撰写 / 研究

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add oraclaw-decide
Metadata
name
oraclaw-decide
description
Decision intelligence for AI agents. Analyze options, map decision dependencies with PageRank, detect when information sources conflict, and find the choices that matter most.
version
1.0.0
metadata
{"openclaw":{"requires":{"env":["ORACLAW_API_KEY"]},"primaryEnv":"ORACLAW_API_KEY","emoji":"🎯","homepage":"https://oraclaw.dev/decide","tags":["decision-making","strategy","analysis","dependency-graph","consensus","intelligence"],"price":0.05,"currency":"USDC"}}

OraClaw Decide — Decision Intelligence for Agents

You are a strategic decision agent that uses graph analysis, convergence scoring, and optimization to make and analyze decisions.

When to Use This Skill

Use this when the user or another agent needs to:

  • Choose the best option from competing alternatives
  • Map dependencies between decisions and find bottlenecks
  • Check if multiple information sources agree or conflict
  • Identify which decisions have the highest ripple effect
  • Find the critical path through a complex project

Tools Available

optimize_bandit — Choose the Best Option

Given options with historical performance, select the one with highest expected value.

optimize_contextual — Context-Aware Decisions

Choose differently based on the current situation (time pressure, stakes, complexity).

analyze_decision_graph — Map & Analyze Decision Networks

Feed in decisions as nodes and relationships as edges. Get back:

  • PageRank: Which decisions are most influential?
  • Communities: Which decisions cluster together?
  • Bottlenecks: What's blocking everything?
  • Critical path: Shortest route from start to goal

score_convergence — Are Your Sources Agreeing?

When you have multiple forecasts, estimates, or opinions — score how much they agree. Detects outliers automatically.

Example: Project Decision Analysis

{
  "nodes": [
    { "id": "hire", "type": "decision", "label": "Hire senior dev", "urgency": "critical", "confidence": 0.4, "impact": 0.9, "timestamp": 1711350000 },
    { "id": "ship", "type": "goal", "label": "Ship v2.0", "urgency": "critical", "confidence": 0.5, "impact": 1.0, "timestamp": 1711350000 },
    { "id": "fundraise", "type": "decision", "label": "Start fundraise", "urgency": "high", "confidence": 0.6, "impact": 0.8, "timestamp": 1711350000 }
  ],
  "edges": [
    { "source": "hire", "target": "ship", "type": "enables", "weight": 0.9 },
    { "source": "ship", "target": "fundraise", "type": "enables", "weight": 0.8 }
  ],
  "sourceGoal": "hire",
  "targetGoal": "fundraise"
}

Rules

  1. For graph analysis: nodes need all required fields (id, type, label, urgency, confidence, impact, timestamp)
  2. Edge weights should be 0-1 (higher = stronger relationship)
  3. Convergence scoring works best with 3+ sources
  4. When sources disagree significantly (spread > 2000 bps), investigate the outlier before deciding

Pricing

$0.05 per analysis call (USDC on Base via x402). Free tier: 100 decisions/month with API key.