feat: WP-0001 foundation + WP-0002 core extensions

WP-0001 — Foundation & GAAF Baseline
- SCOPE.md, ARCHITECTURE-LAYERS.md, contracts/ tree
- .claude/rules/ stubs filled (architecture, stack, boundary)
- 57 tests (pytest), pyproject.toml with ruff+mypy, CI workflow

WP-0002 — Core Extensions (FR-4 + FR-3)
- FR-4: BudgetTracker (thread-safe) + LLMBudgetExceededError +
  optional RunConfig.budget_tracker + enforcement in all adapters
- FR-3: async_execute_prompt on LLMAdapter ABC (asyncio.to_thread
  fallback) + native asyncio.create_subprocess_exec in ClaudeCodeAdapter

81 tests passing.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

llm_connect/adapter.py

@@ -5,10 +5,11 @@ Implements abstraction layer for LLM integration, supporting
 multiple providers (OpenAI, Anthropic, local models, etc.).
 """
 
+import asyncio
 from abc import ABC, abstractmethod
 from typing import Dict, Any
 
-from llm_connect.models import RunConfig, LLMResponse
+from llm_connect.models import RunConfig, LLMResponse, BudgetTracker
 
 
 class LLMAdapter(ABC):
@@ -40,6 +41,26 @@ class LLMAdapter(ABC):
         """
         pass
 
+    async def async_execute_prompt(
+        self,
+        prompt: str,
+        config: RunConfig,
+    ) -> LLMResponse:
+        """Execute a prompt asynchronously.
+
+        Default implementation runs :meth:`execute_prompt` in a thread
+        executor so that the event loop is not blocked. Subclasses may
+        override with a native ``asyncio``-based implementation.
+
+        Args:
+            prompt: Compiled prompt text
+            config: Execution configuration
+
+        Returns:
+            LLMResponse with generated content
+        """
+        return await asyncio.to_thread(self.execute_prompt, prompt, config)
+
     @abstractmethod
     def validate_config(self, config: RunConfig) -> bool:
         """
@@ -53,6 +74,27 @@ class LLMAdapter(ABC):
         """
         pass
 
+    # ── Budget helpers (call in execute_prompt implementations) ─────
+
+    def _preflight_budget(self, config: RunConfig) -> None:
+        """Raise ``LLMBudgetExceededError`` if the budget is already exhausted."""
+        if config.budget_tracker is not None and config.budget_tracker.remaining() == 0:
+            from llm_connect.exceptions import LLMBudgetExceededError
+            tracker = config.budget_tracker
+            raise LLMBudgetExceededError(
+                "Token budget exhausted before making request",
+                total=tracker.total,
+                spent=tracker.spent,
+                requested=0,
+                context={"total": tracker.total, "spent": tracker.spent},
+            )
+
+    def _consume_budget(self, config: RunConfig, response: LLMResponse) -> None:
+        """Consume tokens from the budget tracker after a successful call."""
+        if config.budget_tracker is not None:
+            tokens = response.usage.get("total_tokens", 0)
+            config.budget_tracker.consume(tokens)
+
 
 class MockLLMAdapter(LLMAdapter):
     """
@@ -88,11 +130,12 @@ class MockLLMAdapter(LLMAdapter):
         Returns:
             Mock LLMResponse
         """
+        self._preflight_budget(config)
         self.call_count += 1
         self.last_prompt = prompt
         self.last_config = config
 
-        return LLMResponse(
+        response = LLMResponse(
             content=self.mock_response,
             model=config.model_name,
             usage={
@@ -103,6 +146,8 @@ class MockLLMAdapter(LLMAdapter):
             finish_reason="stop",
             metadata={"mock": True},
         )
+        self._consume_budget(config, response)
+        return response
 
     def validate_config(self, config: RunConfig) -> bool:
         """