Add Phase 7: polish and hardening — retry, truncation, sessions, shutdown

- Config extensions: retry backoff, truncation threshold, session persistence
- LLM retry with exponential backoff + jitter on transient errors (5xx, connection)
- Conversation truncation: drops oldest messages preserving first user + recent N
- Session persistence: auto-save/restore with atomic writes, cleanup of old files
- Graceful shutdown: SIGTERM handler, cancel() on AgentLoop, save-on-exit
- Partial message recovery on mid-stream interruption
- New slash commands: /save, /session
- 18 new tests (5 retry, 5 truncation, 4 session, 4 integration workflows)
- README.md and docs/tools.md documentation

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

tests/integration/conftest.py

@@ -0,0 +1,150 @@
+"""Shared fixtures for integration tests."""
+
+import json
+from collections.abc import AsyncIterator
+from pathlib import Path
+from typing import Any
+from unittest.mock import AsyncMock
+
+import pytest
+
+from app.models.config import AgentConfig, AppConfig, DisplayConfig, LLMConfig, PermissionsConfig, SessionConfig
+from app.models.message import Message
+from app.services.llm import LLMClient
+
+
+@pytest.fixture
+def tmp_workspace(tmp_path: Path) -> Path:
+    """Create a temporary workspace directory with a sample file."""
+    ws = tmp_path / "workspace"
+    ws.mkdir()
+    (ws / "hello.txt").write_text("Hello, world!")
+    return ws
+
+
+@pytest.fixture
+def test_config(tmp_workspace: Path) -> AppConfig:
+    """AppConfig suitable for integration tests."""
+    return AppConfig(
+        llm=LLMConfig(
+            model="test-model",
+            endpoint="http://localhost:11434",
+            max_retries=2,
+            retry_backoff_base=0.01,
+            retry_backoff_max=0.02,
+        ),
+        agent=AgentConfig(
+            max_iterations=10,
+            max_conversation_tokens=32000,
+            workspace_root=tmp_workspace,
+            truncation_keep_recent=4,
+            truncation_threshold=0.85,
+        ),
+        permissions=PermissionsConfig(
+            auto_approve=["read_file", "list_dir", "grep_files", "find_files", "finish"],
+        ),
+        display=DisplayConfig(
+            show_tool_calls=False,
+            show_token_usage=False,
+            stream_output=False,
+        ),
+        session=SessionConfig(
+            session_dir=tmp_workspace / ".sneakycode" / "sessions",
+        ),
+    )
+
+
+def make_text_chunks(content: str) -> list[dict[str, Any]]:
+    """Create SSE chunk dicts for a plain text response."""
+    chunks = []
+    for char in content:
+        chunks.append({
+            "choices": [{"delta": {"content": char}, "index": 0}]
+        })
+    chunks.append({
+        "choices": [{"delta": {}, "finish_reason": "stop", "index": 0}],
+        "usage": {"prompt_tokens": 10, "completion_tokens": len(content), "total_tokens": 10 + len(content)},
+    })
+    return chunks
+
+
+def make_tool_call_chunks(name: str, args: dict[str, Any], tc_id: str = "call_001") -> list[dict[str, Any]]:
+    """Create SSE chunk dicts for a tool call response."""
+    args_str = json.dumps(args)
+    chunks = [
+        {
+            "choices": [{
+                "delta": {
+                    "tool_calls": [{
+                        "index": 0,
+                        "id": tc_id,
+                        "function": {"name": name, "arguments": ""},
+                    }]
+                },
+                "index": 0,
+            }]
+        },
+        {
+            "choices": [{
+                "delta": {
+                    "tool_calls": [{
+                        "index": 0,
+                        "function": {"arguments": args_str},
+                    }]
+                },
+                "index": 0,
+            }]
+        },
+        {
+            "choices": [{"delta": {}, "finish_reason": "tool_calls", "index": 0}],
+            "usage": {"prompt_tokens": 10, "completion_tokens": 20, "total_tokens": 30},
+        },
+    ]
+    return chunks
+
+
+class MockLLMClient:
+    """LLM client that returns scripted SSE chunk sequences."""
+
+    def __init__(self, responses: list[list[dict[str, Any]]]) -> None:
+        self._responses = list(responses)
+        self._call_count = 0
+
+    async def stream_chat(
+        self,
+        messages: list[Message],
+        tools: list[dict[str, Any]] | None = None,
+    ) -> AsyncIterator[dict]:
+        if self._call_count >= len(self._responses):
+            raise RuntimeError("MockLLMClient ran out of scripted responses")
+        chunks = self._responses[self._call_count]
+        self._call_count += 1
+        for chunk in chunks:
+            yield chunk
+
+    async def stream_chat_with_retry(
+        self,
+        messages: list[Message],
+        tools: list[dict[str, Any]] | None = None,
+    ) -> AsyncIterator[dict]:
+        async for chunk in self.stream_chat(messages, tools=tools):
+            yield chunk
+
+    @property
+    def call_count(self) -> int:
+        return self._call_count
+
+    async def close(self) -> None:
+        pass
+
+    async def __aenter__(self):
+        return self
+
+    async def __aexit__(self, *exc):
+        pass
+
+
+@pytest.fixture
+def mock_llm_client():
+    """Factory fixture for creating MockLLMClient instances."""
+    return MockLLMClient