diff --git a/README.md b/README.md
index 21265bb..a98fa60 100644
--- a/README.md
+++ b/README.md
@@ -9,6 +9,8 @@ What you get in this MVP:
 - Privacy budget accounting and audit logging.
 - Tiny ROS 2 adapter placeholder and TLS-configured transport scaffolding (ready to integrate with real ROS2 adapters).
 - Tests validating cross-fleet optimization flow and privacy budgeting.
+- Lightweight DSL seeds for LocalRobotPlan/SharedSignals/PlanDelta (core/dsl.py)
+- Toy adapters for interoperability (adapters/ros2_adapter.py and adapters/gazebo_adapter.py)
 
 How to run tests
 - Install dependencies (if any): this MVP uses only the standard library for tests, but you can install pytest if you wish to run externally.
diff --git a/adapters/gazebo_adapter.py b/adapters/gazebo_adapter.py
new file mode 100644
index 0000000..3184764
--- /dev/null
+++ b/adapters/gazebo_adapter.py
@@ -0,0 +1,16 @@
+from __future__ import annotations
+
+
+class GazeboAdapter:
+    """Placeholder Gazebo adapter for simulation-based testing."""
+
+    def __init__(self, tls_config: dict | None = None) -> None:
+        self.tls_config = tls_config or {}
+
+    def publish_signal(self, contract_id: str, signals: dict) -> bool:
+        # In a full implementation, publish to Gazebo topics or services
+        return True
+
+    def subscribe_signals(self, contract_id: str) -> dict:
+        # Return a minimal, empty signals payload for the MVP bootstrap
+        return {}
diff --git a/core/dsl.py b/core/dsl.py
new file mode 100644
index 0000000..976162e
--- /dev/null
+++ b/core/dsl.py
@@ -0,0 +1,55 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import List, Dict, Any
+
+@dataclass
+class LocalRobotPlanDSL:
+    fleet_id: str
+    robot_id: str
+    tasks: List[str]
+    path: List[Dict[str, float]]
+    objectives: Dict[str, Any]
+
+    def to_model(self):
+        # Lightweight bridge to core LocalRobotPlan model
+        from .models import LocalRobotPlan
+        return LocalRobotPlan(
+            fleet_id=self.fleet_id,
+            robot_id=self.robot_id,
+            tasks=self.tasks,
+            path=self.path,
+            objectives=self.objectives,
+        )
+
+@dataclass
+class SharedSignalsDSL:
+    signals: Dict[str, float]
+    provenance: str | None = None
+    timestamp: float | None = None
+
+    def to_model(self):
+        from .models import SharedSignals
+        return SharedSignals(signals=self.signals, provenance=self.provenance, timestamp=self.timestamp)
+
+@dataclass
+class PlanDeltaDSL:
+    delta_id: str
+    fleet_id: str
+    changes: Dict[str, Any]
+    version: int = 1
+    nonce: str | None = None
+    timestamp: float | None = None
+
+    def to_model(self):
+        from .models import PlanDelta
+        return PlanDelta(
+            delta_id=self.delta_id,
+            fleet_id=self.fleet_id,
+            changes=self.changes,
+            version=self.version,
+            nonce=self.nonce,
+            timestamp=self.timestamp,
+        )
+
+__all__ = ["LocalRobotPlanDSL", "SharedSignalsDSL", "PlanDeltaDSL"]