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+# World-Aware CrewAI Crew
+
+A multi-agent crew where every agent shares the same real-time world context. The research analyst, risk officer, and briefing writer all see the same calibrated probabilities — no contradictions.
+
+## The Problem
+
+In a multi-agent crew, each agent hallucinates different numbers. The researcher says "recession probability is low." The risk officer says "recession probability is elevated." They're not disagreeing — they just have different training data cutoffs.
+
+## The Solution
+
+Fetch real-time world state from prediction markets once, share it across all agents. Data comes from [SimpleFunctions](https://simplefunctions.dev/world) — 9,706 contracts on Kalshi (CFTC-regulated) and Polymarket. No API key needed.
+
+## Setup
+
+```bash
+pip install -r requirements.txt
+export OPENAI_API_KEY=sk-...
+```
+
+## Run
+
+```bash
+python main.py
+```
+
+## Architecture
+
+```
+SimpleFunctions World API (one call, ~800 tokens)
+    ↓
+Shared Context (all agents see same probabilities)
+    ↓
+┌─────────────────┐   ┌─────────────────┐   ┌─────────────────┐
+│   Researcher     │ → │  Risk Officer    │ → │  Briefing Writer │
+│  - world_state   │   │  - world_state   │   │  (context from   │
+│  - search_markets│   │  - market_detail │   │   both agents)   │
+└─────────────────┘   └─────────────────┘   └─────────────────┘
+```
+
+## Output Example
+
+Instead of vague hedging:
+> "Geopolitical tensions remain elevated. We recommend monitoring the situation."
+
+You get data-driven briefings:
+> "Iran invasion probability: 53% (+5c). Hormuz disruption: 95%. Oil at $127 (+3.2%). Geopolitical Risk: 85/100. Recession: 33%. Primary risk: unhedged energy exposure. Action: review commodity hedges by EOD."
+
+## Tools
+
+| Tool | Description |
+|------|-------------|
+| `get_focused_world_state` | Deeper coverage of specific topics |
+| `search_prediction_markets` | Find specific contracts by keyword |
+| `get_market_detail` | Orderbook depth and thesis edges for a contract |
diff --git a/integrations/simplefunctions-world-model/main.py b/integrations/simplefunctions-world-model/main.py
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+"""
+World-Aware CrewAI Crew — Multi-agent system with shared real-time world context.
+
+Problem: In a multi-agent crew, each agent hallucinates different numbers.
+The researcher says "recession probability is low," the risk officer says
+"recession probability is elevated." They're not disagreeing — they just
+have different training data cutoffs.
+
+Solution: Fetch real-time world state from prediction markets once, share
+it across all agents. Everyone cites the same calibrated probabilities.
+
+Data source: SimpleFunctions (https://simplefunctions.dev/world)
+  - 9,706 prediction markets from Kalshi + Polymarket
+  - No API key needed — free and public
+  - ~800 tokens, updated every 15 minutes
+"""
+
+import requests
+from crewai import Agent, Task, Crew
+from crewai.tools import tool
+
+
+# ── Shared world context ───────────────────────────────────────────────────────
+
+world = requests.get("https://simplefunctions.dev/api/agent/world").text
+
+SHARED_CONTEXT = f"""You have access to real-time world data from prediction markets.
+Use the numbers below as ground truth. Do NOT hallucinate probabilities.
+Cite specific contract prices and probabilities directly.
+When citing data, mention the source: SimpleFunctions World Model.
+
+{world}"""
+
+
+# ── Tools ──────────────────────────────────────────────────────────────────────
+
+@tool("get_focused_world_state")
+def get_focused_world_state(topics: str) -> str:
+    """Get world state focused on specific topics for deeper coverage.
+
+    Same token budget, concentrated on fewer topics — more contracts per topic.
+
+    Args:
+        topics: Comma-separated topics, e.g. 'geopolitics,energy'.
+                Options: geopolitics, economy, energy, elections, crypto, tech.
+    """
+    return requests.get(
+        f"https://simplefunctions.dev/api/agent/world?focus={topics}"
+    ).text
+
+
+@tool("search_prediction_markets")
+def search_prediction_markets(query: str) -> str:
+    """Search for specific prediction market contracts across Kalshi and Polymarket.
+
+    Args:
+        query: Natural language query, e.g. 'iran oil', 'fed rate cut', 'bitcoin'.
+    """
+    import json
+    resp = requests.get(
+        f"https://simplefunctions.dev/api/public/scan?q={query}&limit=10"
+    )
+    return json.dumps(resp.json().get("markets", [])[:10], indent=2)
+
+
+@tool("get_market_detail")
+def get_market_detail(ticker: str) -> str:
+    """Get detailed data for a specific prediction market contract.
+
+    Includes price, spread, volume, orderbook depth, and related thesis edges.
+
+    Args:
+        ticker: Kalshi ticker (e.g. KXIRANINVASION) or Polymarket condition ID.
+    """
+    import json
+    resp = requests.get(
+        f"https://simplefunctions.dev/api/public/market/{ticker}?depth=true"
+    )
+    return json.dumps(resp.json(), indent=2)
+
+
+# ── Agents ─────────────────────────────────────────────────────────────────────
+
+researcher = Agent(
+    role="Macro Research Analyst",
+    goal="Analyze geopolitical and economic developments using real-time probability data",
+    backstory=SHARED_CONTEXT
+    + "\nYou are a senior macro analyst at a global macro fund. You cite specific "
+    "probabilities and prices from prediction markets. You never say 'approximately' "
+    "when you have exact numbers. You identify the most important risks and opportunities.",
+    verbose=True,
+)
+
+risk_officer = Agent(
+    role="Risk Officer",
+    goal="Identify portfolio risks based on current world conditions",
+    backstory=SHARED_CONTEXT
+    + "\nYou are a risk officer. You flag when probabilities cross thresholds that "
+    "matter for portfolio exposure. You reference specific contract prices. You never "
+    "say 'could' when you have a specific probability.",
+    verbose=True,
+)
+
+writer = Agent(
+    role="Morning Briefing Writer",
+    goal="Produce a concise morning briefing for the investment committee",
+    backstory=SHARED_CONTEXT
+    + "\nYou write crisp, data-driven briefings for busy portfolio managers. Every "
+    "claim has a number attached. No hedging language. No filler. 200 words max.",
+    verbose=True,
+)
+
+
+# ── Tasks ──────────────────────────────────────────────────────────────────────
+
+research_task = Task(
+    description=(
+        "Analyze the current geopolitical and economic situation. Focus on: "
+        "1) The top geopolitical risk and its probability, "
+        "2) Recession and Fed rate expectations, "
+        "3) Energy market conditions. "
+        "Use the world state data and search for specific contracts if needed. "
+        "Cite every number with its source contract."
+    ),
+    expected_output="Structured analysis with specific probability citations from prediction markets",
+    agent=researcher,
+    tools=[get_focused_world_state, search_prediction_markets],
+)
+
+risk_task = Task(
+    description=(
+        "Based on the research analysis, identify the top 3 portfolio risks right now. "
+        "For each risk: state the specific prediction market probability, explain why "
+        "it matters for portfolio exposure, and recommend one action."
+    ),
+    expected_output="3 risks with probability levels, portfolio implications, and actions",
+    agent=risk_officer,
+    tools=[get_focused_world_state, get_market_detail],
+    context=[research_task],
+)
+
+briefing_task = Task(
+    description=(
+        "Write a 200-word morning briefing combining the research and risk analysis. "
+        "Rules: every sentence must contain a number. No hedging. No filler. "
+        "End with the single most important thing the PM should do today."
+    ),
+    expected_output="200-word morning briefing with data citations",
+    agent=writer,
+    context=[research_task, risk_task],
+)
+
+
+# ── Crew ───────────────────────────────────────────────────────────────────────
+
+crew = Crew(
+    agents=[researcher, risk_officer, writer],
+    tasks=[research_task, risk_task, briefing_task],
+    verbose=True,
+)
+
+
+if __name__ == "__main__":
+    print("Starting world-aware macro crew...")
+    print(f"World state loaded: {len(world)} characters\n")
+    result = crew.kickoff()
+    print("\n" + "=" * 60)
+    print("MORNING BRIEFING")
+    print("=" * 60)
+    print(result)
diff --git a/integrations/simplefunctions-world-model/requirements.txt b/integrations/simplefunctions-world-model/requirements.txt
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+crewai>=0.152.0
+crewai-tools>=0.38.0
+requests>=2.31.0