build(agent): new-agents-4#58ba63 iteration

README.md

@@ -12,3 +12,9 @@ Getting started
 - The repository uses a minimal in-tree packaging setup (Python) and PyTest-based tests.
 
 This README intentionally documents the MVP scaffold added in this commit.
+
+Blueprints and Starter Interoperability
+- This repository includes a minimal adapter blueprint and a toy cross-venue analytics pipeline to bootstrap MercuryMesh interoperability across ecosystems.
+- blueprint/adapter_blueprint.py: A lean, copy-paste friendly adapter skeleton showing how to connect, extract signals, and emit MarketSignal-like payloads.
+- blueprint/toy_cross_venue_pipeline.py: A tiny end-to-end example that simulates two venues and merges signals into an AggregatedSignal with a deterministic, offline-friendly merge strategy.
+- You can adapt these templates to fit into your existing adapters and contract graph workflow.

blueprint/adapter_blueprint.py

@@ -0,0 +1,100 @@
+"""
+Adapter Blueprint for MercuryMesh MVP
+This module provides a minimal, well-documented skeleton that teams can copy
+when implementing new venue adapters. It is intentionally simple and self-contained
+so it can be dropped into new repos or integrated into the existing codebase with
+minimal friction.
+
+The blueprint focuses on three responsibilities:
+- Connect to a venue feed (simulated or real)
+- Extract raw venue data and normalize it into a common signal format
+- Emit a Signal contract compatible object that downstream components can consume
+
+Note: This is a blueprint, not a fully-featured adapter. It lacks networking,
+security, and production-grade error handling which should be added in production use.
+"""
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Dict, Any, Optional
+import time
+
+
+@dataclass
+class LocalMarketContext:
+    venue_id: str
+    symbol: str
+    timeframe: str
+
+
+@dataclass
+class MarketSignal:
+    venue_id: str
+    symbol: str
+    timestamp: float
+    features: Dict[str, float]
+
+
+class AdapterBlueprint:
+    """Minimal adapter blueprint.
+
+    - venue_id: identifier for the venue this adapter connects to
+    - registry: optional contract/GoC registry payload (not required for the blueprint)
+    """
+
+    def __init__(self, venue_id: str, registry: Optional[Dict[str, Any]] = None) -> None:
+        self.venue_id = venue_id
+        self.registry = registry or {}
+        self.connected = False
+
+    def connect(self) -> bool:
+        """Simulate a connection to the venue feed.
+
+        In a real adapter this would establish a network connection, authenticate, etc.
+        For the blueprint, we simply mark as connected and return True.
+        """
+        # In a real implementation, add try/except and reconnection logic
+        self.connected = True
+        return self.connected
+
+    def fetch_raw(self) -> Any:
+        """Fetch a raw payload from the venue feed (simulated).
+
+        Returns a simple dict that a concrete subclass would parse.
+        """
+        if not self.connected:
+            raise RuntimeError("Adapter not connected to venue feed")
+        # Simulated raw payload; in practice this would be a socket/HTTP feed, etc.
+        now = time.time()
+        return {
+            "venue": self.venue_id,
+            "symbol": "XYZ",
+            "ts": now,
+            "raw_features": {
+                "liquidity_proxy": 0.9,
+                "order_flow_intensity": 0.6,
+                "volatility_proxy": 1.1,
+            },
+        }
+
+    def extract_signal(self, raw: Any) -> MarketSignal:
+        """Normalize and map raw payload to a MarketSignal contract."""
+        venue = str(raw.get("venue", self.venue_id))
+        symbol = str(raw.get("symbol", "UNKNOWN"))
+        timestamp = float(raw.get("ts", time.time()))
+        features = dict(raw.get("raw_features", {}))
+        return MarketSignal(venue_id=venue, symbol=symbol, timestamp=timestamp, features=features)
+
+    def emit(self, signal: MarketSignal) -> MarketSignal:
+        """Hook for downstream consumers. In a real adapter this might publish to a bus."""
+        # For blueprint purposes, simply return the signal to show it was produced
+        return signal
+
+
+if __name__ == "__main__":
+    # Simple demonstration when run as a script
+    adapter = AdapterBlueprint(venue_id="venue_example")
+    adapter.connect()
+    raw = adapter.fetch_raw()
+    sig = adapter.extract_signal(raw)
+    print("Blueprint adapter produced signal:", sig)

blueprint/toy_cross_venue_pipeline.py

@@ -0,0 +1,91 @@
+"""
+Toy cross-venue analytics pipeline
+This script demonstrates a very small, deterministic cross-venue merge
+workflow that mirrors the MVP idea of aggregating signals from multiple venues
+without sharing raw data.
+
+It is intentionally lightweight and self-contained to serve as a starter.
+Run: python3 blueprint/toy_cross_venue_pipeline.py
+"""
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Dict, List
+import time
+
+
+@dataclass
+class LocalMarketContext:
+    venue_id: str
+    symbol: str
+    timeframe: str
+
+
+@dataclass
+class MarketSignal:
+    venue_id: str
+    symbol: str
+    timestamp: float
+    features: Dict[str, float]
+
+
+@dataclass
+class AggregatedSignal:
+    venue_set: List[str]
+    feature_vector: Dict[str, float]
+    privacy_budget_used: float
+    nonce: int
+
+
+def simulate_two_venues() -> List[MarketSignal]:
+    now = time.time()
+    sigs = [
+        MarketSignal(
+            venue_id="venue-A",
+            symbol="ABC",
+            timestamp=now,
+            features={"liquidity_proxy": 0.82, "order_flow_intensity": 0.55, "volatility_proxy": 1.15},
+        ),
+        MarketSignal(
+            venue_id="venue-B",
+            symbol="ABC",
+            timestamp=now,
+            features={"liquidity_proxy": 0.78, "order_flow_intensity": 0.60, "volatility_proxy": 1.10},
+        ),
+    ]
+    return sigs
+
+
+def aggregate_signals(signals: List[MarketSignal]) -> AggregatedSignal:
+    if not signals:
+        return AggregatedSignal(venue_set=[], feature_vector={}, privacy_budget_used=0.0, nonce=0)
+    # Simple averaging across venues for each feature
+    keys = set().union(*(s.features.keys() for s in signals))
+    avg = {k: 0.0 for k in keys}
+    for s in signals:
+        for k in keys:
+            avg[k] = avg[k] + s.features.get(k, 0.0)
+    n = float(len(signals))
+    feature_vector = {k: (v / n) for k, v in avg.items()}
+    privacy_budget_used = min([s.features.get("privacy_budget", 0.0) for s in signals] or [0.0])
+    return AggregatedSignal(venue_set=[s.venue_id for s in signals], feature_vector=feature_vector, privacy_budget_used=privacy_budget_used, nonce=int(now_epoch()) )
+
+
+def now_epoch() -> int:
+    return int(time.time())
+
+
+def main():
+    signals = simulate_two_venues()
+    agg = aggregate_signals(signals)
+    print("Toy AggregatedSignal")
+    print("  venues:", agg.venue_set)
+    print("  features:")
+    for k, v in agg.feature_vector.items():
+        print(f"    {k}: {v:.4f}")
+    print("  privacy_budget_used:", agg.privacy_budget_used)
+    print("  nonce:", agg.nonce)
+
+
+if __name__ == "__main__":
+    main()