chore: import upstream snapshot with attribution

docs/zh/s08-background-tasks.md

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+# s08: Background Tasks (后台任务)
+
+`s01 > s02 > s03 > s04 > s05 > s06 | s07 > [ s08 ] s09 > s10 > s11 > s12`
+
+> *"慢操作丢后台, agent 继续想下一步"* -- 后台线程跑命令, 完成后注入通知。
+>
+> **Harness 层**: 后台执行 -- 模型继续思考, harness 负责等待。
+
+## 问题
+
+有些命令要跑好几分钟: `npm install`、`pytest`、`docker build`。阻塞式循环下模型只能干等。用户说 "装依赖, 顺便建个配置文件", Agent 却只能一个一个来。
+
+## 解决方案
+
+```
+Main thread                Background thread
++-----------------+        +-----------------+
+| agent loop      |        | subprocess runs |
+| ...             |        | ...             |
+| [LLM call] <---+------- | enqueue(result) |
+|  ^drain queue   |        +-----------------+
++-----------------+
+
+Timeline:
+Agent --[spawn A]--[spawn B]--[other work]----
+             |          |
+             v          v
+          [A runs]   [B runs]      (parallel)
+             |          |
+             +-- results injected before next LLM call --+
+```
+
+## 工作原理
+
+1. BackgroundManager 用线程安全的通知队列追踪任务。
+
+```python
+class BackgroundManager:
+    def __init__(self):
+        self.tasks = {}
+        self._notification_queue = []
+        self._lock = threading.Lock()
+```
+
+2. `run()` 启动守护线程, 立即返回。
+
+```python
+def run(self, command: str) -> str:
+    task_id = str(uuid.uuid4())[:8]
+    self.tasks[task_id] = {"status": "running", "command": command}
+    thread = threading.Thread(
+        target=self._execute, args=(task_id, command), daemon=True)
+    thread.start()
+    return f"Background task {task_id} started"
+```
+
+3. 子进程完成后, 结果进入通知队列。
+
+```python
+def _execute(self, task_id, command):
+    try:
+        r = subprocess.run(command, shell=True, cwd=WORKDIR,
+            capture_output=True, text=True, timeout=300)
+        output = (r.stdout + r.stderr).strip()[:50000]
+    except subprocess.TimeoutExpired:
+        output = "Error: Timeout (300s)"
+    with self._lock:
+        self._notification_queue.append({
+            "task_id": task_id, "result": output[:500]})
+```
+
+4. 每次 LLM 调用前排空通知队列。
+
+```python
+def agent_loop(messages: list):
+    while True:
+        notifs = BG.drain_notifications()
+        if notifs:
+            notif_text = "\n".join(
+                f"[bg:{n['task_id']}] {n['result']}" for n in notifs)
+            messages.append({"role": "user",
+                "content": f"<background-results>\n{notif_text}\n"
+                           f"</background-results>"})
+        response = client.messages.create(...)
+```
+
+循环保持单线程。只有子进程 I/O 被并行化。
+
+## 相对 s07 的变更
+
+| 组件           | 之前 (s07)       | 之后 (s08)                         |
+|----------------|------------------|------------------------------------|
+| Tools          | 8                | 6 (基础 + background_run + check)  |
+| 执行方式       | 仅阻塞           | 阻塞 + 后台线程                    |
+| 通知机制       | 无               | 每轮排空的队列                     |
+| 并发           | 无               | 守护线程                           |
+
+## 试一试
+
+```sh
+cd learn-claude-code
+python agents/s08_background_tasks.py
+```
+
+试试这些 prompt (英文 prompt 对 LLM 效果更好, 也可以用中文):
+
+1. `Run "sleep 5 && echo done" in the background, then create a file while it runs`
+2. `Start 3 background tasks: "sleep 2", "sleep 4", "sleep 6". Check their status.`
+3. `Run pytest in the background and keep working on other things`