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* feat: s01-s14 docs quality overhaul — tool pipeline, single-agent, knowledge & resilience Rewrite code.py and README (zh/en/ja) for s01-s14, each chapter building incrementally on the previous. Key fixes across chapters: - s01-s04: agent loop, tool dispatch, permission pipeline, hooks - s05-s08: todo write, subagent, skill loading, context compact - s09-s11: memory system, system prompt assembly, error recovery - s12-s14: task graph, background tasks, cron scheduler All chapters CC source-verified. Code inherits fixes forward (PROMPT_SECTIONS, json.dumps cache, real-state context, can_start dep protection, etc.). * feat: s15-s19 docs quality overhaul — multi-agent platform: teams, protocols, autonomy, worktree, MCP tools Rewrite code.py and README (zh/en/ja) for s15-s19, the multi-agent platform chapters. Each chapter inherits all previous fixes and adds one mechanism: - s15: agent teams (TeamCreate, teammate threads, shared task list) - s16: team protocols (plan approval, shutdown handshake, consume_inbox) - s17: autonomous agents (idle polling, auto-claim, consume_lead_inbox) - s18: worktree isolation (git worktree, bind_task, cwd switching, safety) - s19: MCP tools (MCPClient, normalize_mcp_name, assemble_tool_pool, no cache) All appendix source code references verified against CC source. Config priority corrected: claude.ai < plugin < user < project < local. * fix: 5 regressions across s05-s19 — glob safety, todo validation, memory extraction, protocol types, dep crash - s05-s09: glob results now filter with is_relative_to(WORKDIR) (inherited from s02) - s06-s08: todo_write validates content/status required fields (inherited from s05) - s09: extract_memories uses pre-compression snapshot instead of compacted messages - s16: submit_plan docstring clarifies protocol-only (not code-level gate) - s17-s19: match_response restores type mismatch validation (from s16) - s17-s19: claim_task deps list handles missing dep files without crashing * fix: s12 Todo V2 logic reversal, s14/s15 cron range validation, s18/s19 worktree name validation - s12 README (zh/en/ja): fix Todo V2 direction — interactive defaults to Task, non-interactive/SDK defaults to TodoWrite. Fix env var name to CLAUDE_CODE_ENABLE_TASKS (not TODO_V2). - s14/s15: add _validate_cron_field with per-field range checks (minute 0-59, hour 0-23, dom 1-31, month 1-12, dow 0-6), step > 0, range lo <= hi. Replace old try/except validation that only caught exceptions. - s18/s19: add validate_worktree_name() to remove_worktree and keep_worktree, not just create_worktree. * fix: align s16-s19 teaching tool consistency * fix pr265 chapter diagrams * Add comprehensive s20 harness chapter * Fix chapter smoke test regressions * Clarify README tutorial track transition --------- Co-authored-by: Haoran <bill-billion@outlook.com>
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# s05: TodoWrite — 没有计划的 Agent，做着做着就偏了
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[中文](README.md) · [English](README.en.md) · [日本語](README.ja.md)
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s01 → s02 → s03 → s04 → `s05` → [s06](../s06_subagent/) → s07 → ... → s20
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> *"没有计划的 agent 走哪算哪"* — 先列步骤再动手，长任务更不容易漏项。
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>
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> **Harness 层**: 规划 — 让 Agent 在动手之前先想清楚。
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---
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## 问题
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给 Agent 一个复杂任务："把所有 Python 文件改成 snake_case 命名，然后跑测试，修好失败。"
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Agent 开始干活，改了 3 个文件，跑了个测试，发现 2 个失败，开始修。修着修着，它忘了最初是"改成 snake_case"，测试失败把注意力全吸走了。
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对话越长越严重：工具结果不断填满上下文，系统提示的影响力被稀释。一个 10 步重构，做完 1-3 步就开始即兴发挥，因为 4-10 步已经被挤出注意力了。
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---
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## 解决方案
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保留上一章的最小 hook 结构，重点看新增的 `todo_write` 工具和 reminder 机制。`todo_write` 本身不做任何实际工作，不能读文件、不能跑命令，只是让 Agent 在动手之前先理清思路。
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dispatch 机制不变，新工具仍然走 `TOOL_HANDLERS[block.name]` 分发。但为了演示 todo reminder，循环里加了一个计数器：连续 3 轮没调 `todo_write` 就注入一条提醒。
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---
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## 工作原理
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**todo_write 工具**，接收一个带状态的列表，持久化到 `.tasks/current_todos.json`（教学版写盘以便观察），同时在终端显示进度：
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```python
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def run_todo_write(todos: list) -> str:
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tasks_file = TASKS_DIR / "current_todos.json"
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tasks_file.write_text(json.dumps(todos, indent=2, ensure_ascii=False))
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lines = ["\n## Current Tasks"]
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for t in todos:
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icon = {"pending": " ", "in_progress": "▸", "completed": "✓"}[t["status"]]
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lines.append(f" [{icon}] {t['content']}")
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print("\n".join(lines))
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return f"Updated {len(todos)} tasks"
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```
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工具定义和其他 5 个工具一起加入 dispatch map：
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```python
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TOOLS = [
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{"name": "bash", ...},
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{"name": "read_file", ...},
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{"name": "write_file", ...},
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{"name": "edit_file", ...},
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{"name": "glob", ...},
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# s05: 新增一条
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{"name": "todo_write", "description": "Create and manage a task list ...",
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"input_schema": {
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"type": "object",
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"properties": {
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"todos": {
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"type": "array",
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"items": {
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"type": "object",
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"properties": {
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"content": {"type": "string"},
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"status": {"type": "string", "enum": ["pending", "in_progress", "completed"]},
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},
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},
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},
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},
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},
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},
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]
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TOOL_HANDLERS["todo_write"] = run_todo_write
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```
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**Nag reminder**，模型连续 3 轮没调 `todo_write` 时，自动注入一条提醒（教学版机制，CC 源码中没有这个固定轮数逻辑）：
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```python
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if rounds_since_todo >= 3 and messages:
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messages.append({
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"role": "user",
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"content": "<reminder>Update your todos.</reminder>",
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})
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rounds_since_todo = 0
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```
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Agent 收到任务后的典型流程：先调 `todo_write` 列出所有步骤（全 `pending`）→ 做一个步骤，改成 `in_progress` → 做完改成 `completed` → 看下一个 `pending` → 继续。连续 3 轮没有调用 `todo_write` 时，循环会在下一次 LLM 调用前追加一条 reminder。
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**关键洞察**：todo_write 不给 Agent 增加任何**执行能力**。它增加的是**规划能力**。
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---
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## 相对 s04 的变更
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| 组件 | 之前 (s04) | 之后 (s05) |
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|------|-----------|-----------|
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| 工具数量 | 5 (bash, read, write, edit, glob) | 6 (+todo_write) |
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| 规划能力 | 无 | 带状态的 TODO 列表 + nag reminder |
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| SYSTEM 提示 | 通用提示 | 加入 "先计划再执行" 引导 |
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| 循环 | 不变 | dispatch 不变，新增 rounds_since_todo 计数器和 reminder 注入 |
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---
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## 试一下
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```sh
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cd learn-claude-code
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python s05_todo_write/code.py
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```
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试试这些 prompt：
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1. `Refactor s05_todo_write/example/hello.py: add type hints, docstrings, and a main guard`（先列 3 步再执行）
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2. `Create a Python package under s05_todo_write/example/demo_pkg with __init__.py, utils.py, and tests/test_utils.py`
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3. `Review Python files under s05_todo_write/example and fix any style issues`
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观察重点：第一次工具调用是不是 `todo_write`？TODO 列了几步？执行过程中状态有没有从 `pending` 变成 `in_progress` / `completed`？
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---
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## 接下来
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Agent 能计划了。但如果一个任务太大，比如"重构整个认证模块"，光靠 TODO 列表不够。这个任务本身就是几十个小任务的集合，放在同一个对话里会被上下文淹没。
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s06 Subagent → 把大任务拆成子任务，每个子任务派一个独立的 Agent。它们有自己的干净上下文，不会互相污染。
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<details>
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<summary>深入 CC 源码</summary>
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CC 中有两套任务系统并存（`tasks.ts:133-139`）：
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- **TodoWrite（V1）**：一个简单的列表工具，数据在内存 AppState 中维护（`TodoWriteTool.ts:65-103`）。教学版写盘到 `.tasks/current_todos.json` 是为了可观察性，真实 V1 不写盘
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- **Task System（V2 = s12）**：文件持久化、依赖图、并发锁、ownership
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切换由 `isTodoV2Enabled()` 控制。当前源码的实现逻辑：交互式会话中 V2 默认启用，非交互式会话（SDK）中 V1 默认启用；设置 `CLAUDE_CODE_ENABLE_TASKS` 环境变量可强制启用 V2。注意源码注释 "Force-enable tasks in non-interactive mode" 描述的是 env var 路径的用途，和默认分支的返回值语义不同，阅读时需区分。
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教学版省略了真实源码中的 `activeForm` 字段（`utils/todo/types.ts:8-15`）。CC 用它给 UI spinner 展示"正在做什么"，教学版只有终端输出，不需要这个字段。
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教学版的 nag reminder（3 轮未更新就注入提醒）是教学机制。CC 源码中没有固定的"3 轮"逻辑，更接近的是 `TodoWriteTool.ts:72-107` 中当 3 个以上 todo 全部完成但没有 verification 项时，追加 verification nudge。
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Task System 相比 TodoWrite 的核心增量：
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- 文件持久化（Claude 配置目录下 `tasks/{taskListId}/{taskId}.json`）而非内存列表
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- `blockedBy` 依赖图而非平铺列表
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- `proper-lockfile` 并发安全而非无锁
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- 四个独立工具（Create/Get/Update/List）而非一个
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- TaskCreated / TaskCompleted hooks（`TaskCreateTool.ts:80-129`、`TaskUpdateTool.ts:231-260`）供外部系统集成
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</details>
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<!-- translation-sync: zh@v1, en@v0, ja@v0 -->
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