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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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# s02: Tool Use — 多加一个工具，只加一行
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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](../s03_permission/) → s04 → ... → s20
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> *"加一个工具, 只加一个 handler"* — 循环不用动, 新工具注册进 dispatch map 就行。
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>
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> **Harness 层**: 工具分发 — 扩展模型能触达的边界。
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---
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## 只有 bash 一个工具
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s01 的 Agent 只有一个 bash 工具。读文件要 `cat`，写文件要 `echo "..." > file.py`，改文件要 `sed`。
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模型想的是"读这个文件"，却要拼出 `cat path/to/file`。多了一层翻译，浪费 token，还容易拼错。
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---
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## 全局视角：工具分发
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s01 的循环完全保留（LLM 调用、stop_reason 判断、消息追加）。唯一的变动在工具执行那 1 行：`run_bash()` 替换为 `TOOL_HANDLERS[block.name]()` 查表分发。
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给 Agent 加一个工具只需要做两件事：
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1. **定义工具**：在 `TOOLS` 数组里加一条描述
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2. **注册处理函数**：在 `TOOL_HANDLERS` 字典里加一个映射
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---
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## 从 1 个工具到 5 个工具
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s01 只有一个 bash：
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```python
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TOOLS = [{"name": "bash", ...}]
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def run_bash(command): ...
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```
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s02 加到 5 个，每个工具都是独立定义：
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```python
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TOOLS = [
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{"name": "bash", "description": "Run a shell command.", ...},
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{"name": "read_file", "description": "Read file contents.", ...},
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{"name": "write_file", "description": "Write content to file.", ...},
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{"name": "edit_file", "description": "Replace text in file once.", ...},
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{"name": "glob", "description": "Find files by pattern.", ...},
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]
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```
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每个工具有自己的实现函数：
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```python
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def run_read(path, limit=None):
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lines = safe_path(path).read_text().splitlines()
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if limit:
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lines = lines[:limit]
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return "\n".join(lines)
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def run_write(path, content):
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safe_path(path).write_text(content)
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return f"Wrote {len(content)} bytes to {path}"
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def run_edit(path, old_text, new_text):
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text = safe_path(path).read_text()
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if old_text not in text:
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return "Error: text not found"
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safe_path(path).write_text(text.replace(old_text, new_text, 1))
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return f"Edited {path}"
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def run_glob(pattern):
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import glob as g
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return "\n".join(g.glob(pattern, root_dir=WORKDIR))
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```
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---
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## 工具分发
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```python
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TOOL_HANDLERS = {
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"bash": run_bash,
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"read_file": run_read,
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"write_file": run_write,
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"edit_file": run_edit,
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"glob": run_glob,
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}
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# 循环里只改了一行——从硬编码 run_bash 变成查表：
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for block in response.content:
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if block.type == "tool_use":
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handler = TOOL_HANDLERS[block.name] # 查表
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output = handler(**block.input) # 调用
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results.append(...)
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```
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加一个工具 = 在 `TOOLS` 数组加一条 + 在 `TOOL_HANDLERS` 字典加一行。循环不变。
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---
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## 多个工具调用
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模型经常一次返回多个 tool_use："读一下 a.py 和 b.py，然后列出所有 .py 文件"。
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教学版按 `response.content` 原始顺序逐个执行。CC 的做法更复杂：按原始顺序切成连续 batch，batch 内并发安全的工具并行执行，batch 间严格顺序（见附录）。
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---
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## 速查
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| 概念 | 一句话 |
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|------|--------|
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| TOOL_HANDLERS | 工具名 → 处理函数的字典。加工具 = 加一行映射 |
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| 工具定义 | 告诉模型"我能做什么"的 JSON schema |
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| 多工具调用 | 模型可一次返回多个 tool_use，教学版按原始顺序逐个执行 |
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| 循环不变 | s01 的 `while True` 循环一行都没改 |
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---
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## 相对 s01 的变更
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| 组件 | 之前 (s01) | 之后 (s02) |
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|------|-----------|-----------|
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| 工具数量 | 1 (bash) | 5 (+read, write, edit, glob) |
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| 工具执行 | 硬编码 `run_bash()` | TOOL_HANDLERS 查表分发 |
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| 路径安全 | 无 | safe_path 校验（仅 file tools） |
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| 循环 | `while True` + `stop_reason` | 与 s01 完全一致 |
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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 s02_tool_use/code.py
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```
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试试这些 prompt：
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1. `Read the file README.md and tell me what this project is about`
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2. `Create a file called test.py that prints "hello", then read it back`
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3. `Find all Python files in this directory`
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4. `Read both README.md and requirements.txt, then create a summary file`
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观察重点：模型什么时候只调一个工具，什么时候一次调多个？多个工具调用的顺序和结果是否正确？
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---
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## 接下来
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现在 Agent 有 5 个专用工具。file tools 受 `safe_path` 保护，但 bash 不受限制，`rm -rf /` 还是能跑。
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s03 Permission → 在工具执行之前加一道门：这个操作安全吗？需要用户批准吗？
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<details>
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<summary>深入 CC 源码</summary>
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> 以下基于 CC 源码 `Tool.ts`、`tools.ts`、`toolOrchestration.ts`、`toolExecution.ts`、`StreamingToolExecutor.ts` 的核查。
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### 一、工具定义方式
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**教学版**：`TOOLS` 数组 + `TOOL_HANDLERS` 字典。定义和实现分开。
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**CC**：每个工具是 `buildTool()` 创建的独立对象，包含 schema、验证、权限、执行。`getAllBaseTools()` 汇总所有工具。
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教学版的分离方式对教学更清晰——读者一眼看到"加一个工具 = 两条定义"。
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### 二、并发安全判断：isConcurrencySafe()
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教学版按原始顺序逐个执行，不做并发。CC 用 `isConcurrencySafe(input)` 判断能否并发——注意这不是简单的"只读 vs 写"，而是按具体输入判断：
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| | isReadOnly | isConcurrencySafe |
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|---|---|---|
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| FileRead | true | true |
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| Glob | true | true |
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| Bash `ls` | true | **true** ← 关键差异 |
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| Bash `rm` | false | false |
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| TaskCreate | false | **true** ← 改状态但可并发（TaskCreate 在 s12 介绍） |
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CC 的 Bash tool 的 `isConcurrencySafe` 等于 `isReadOnly`——只读命令可并发，写命令不可。TaskCreate 虽然改了任务文件，但每次都写不同的文件，所以可以并发。
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### 三、分区算法
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CC 的 `partitionToolCalls()`（`toolOrchestration.ts:91-115`）不是分两组，而是把工具调用**按连续块分批**：
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```
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[read A, read B, glob *.py, bash "rm x", read C]
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→ batch1(并发): [read A, read B, glob *.py]
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→ batch2(串行): [bash "rm x"]
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→ batch3(并发): [read C]
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```
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并发安全的连续块编入同一个 batch，batch 内真正并发执行（`toolOrchestration.ts:152-176`，有并发上限）。遇到非并发安全的就开新 batch 串行执行。batch 之间严格顺序。
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### 四、验证管线
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CC 的每个工具调用经过严格的 5 步验证（`toolExecution.ts`）：
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1. **Zod schema 验证**（`614-680`，教学版用 JSON Schema 替代）：参数类型/结构检查
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2. **工具级 validateInput()**（`682-733`）：参数值验证（如路径是否在工作区内）
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3. **PreToolUse hooks**（`800-862`，s04 详细介绍）：钩子可以返回消息、修改输入、阻止执行
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4. **权限检查**（`921-931`，s03 的核心内容）：canUseTool + checkPermissions → allow/deny/ask
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5. **执行 tool.call()**（`1207-1222`）
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教学版省略了 Zod（用 JSON Schema）、省略了 validateInput（用安全函数）、保留了权限检查和钩子概念。
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### 五、流式工具执行
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CC 的 `StreamingToolExecutor`（`StreamingToolExecutor.ts`）让工具在模型还在生成时就启动——不等模型说完。`read_file` 可能在模型还在输出"我来分析"的时候就跑完了。教学版不实现这个，目标和 s01 一致——概念清晰，不追求性能极致。
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### 六、工具结果持久化
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每个工具有一个 `maxResultSizeChars` 字段。结果超过这个值就落盘，模型看到的是预览 + 文件路径。FileRead 特殊——设为 `Infinity`，防止读文件的输出又被当成文件落盘。具体来说，如果 FileRead 的结果超过阈值被落盘，模型下次读那个落盘文件时又会触发落盘 → 无限循环（读文件 → 落盘 → 再读 → 再落盘 → ...）。
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</details>
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<!-- translation-sync: zh@v1, en@v0, ja@v0 -->
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