feat: implement DCOS source tree, tests, and build configuration

Complete implementation of the DCOS package including:
- 40+ Python source files across agents, communication, core, learning, memory, protocols, utils
- pyproject.toml build configuration
- 102 unit tests across all subsystems
- Fixed flake.nix (Python 3.12, proper dependencies, pyproject build)
- Fixed .woodpecker.yml (correct paths, removed silent-fail flags)
- Added .gitignore
- Cleared stale pytest cache

src/dcos/core/allocator.py

@@ -0,0 +1,45 @@
+"""
+Resource allocator — manages compute and memory resource distribution among agents.
+"""
+
+from __future__ import annotations
+from typing import Dict, List, Optional, Tuple
+
+
+class ResourceAllocator:
+    """Allocates system resources (compute, memory, bandwidth) among agents."""
+
+    def __init__(self) -> None:
+        self._total_cpu: float = 100.0
+        self._total_memory: float = 1024.0
+        self._allocations: Dict[str, Dict[str, float]] = {}
+
+    def allocate(self, agent_id: str, cpu: float, memory: float) -> bool:
+        if cpu <= 0 or memory <= 0:
+            return False
+        remaining_cpu = self._total_cpu - sum(
+            a.get("cpu", 0) for a in self._allocations.values()
+        )
+        remaining_memory = self._total_memory - sum(
+            a.get("memory", 0) for a in self._allocations.values()
+        )
+        if cpu > remaining_cpu or memory > remaining_memory:
+            return False
+        self._allocations[agent_id] = {"cpu": cpu, "memory": memory}
+        return True
+
+    def release(self, agent_id: str) -> bool:
+        return agent_id in self._allocations and bool(
+            self._allocations.pop(agent_id, None)
+        )
+
+    def get_allocation(self, agent_id: str) -> Dict[str, float]:
+        return self._allocations.get(agent_id, {"cpu": 0.0, "memory": 0.0})
+
+    def utilization(self) -> Dict[str, float]:
+        total_cpu = sum(a.get("cpu", 0) for a in self._allocations.values())
+        total_mem = sum(a.get("memory", 0) for a in self._allocations.values())
+        return {
+            "cpu": total_cpu / self._total_cpu,
+            "memory": total_mem / self._total_memory,
+        }