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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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gui-yue
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s02_tool_use/README.en.md
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# s02: Tool Use — Add a Tool, Add Just One Line
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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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> *"Add a tool, add just one handler"* — The loop stays the same. Register the new tool in the dispatch map and you're done.
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>
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> **Harness Layer**: Tool Dispatch — Expanding the model's reach.
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---
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## Only One Tool: Bash
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The s01 Agent has only one tool: bash. To read a file, `cat`; to write, `echo "..." > file.py`; to edit, `sed`.
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The model thinks "read this file" but has to spell out `cat path/to/file`. An extra layer of translation that wastes tokens and invites errors.
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---
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## Overview: Tool Dispatch
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The s01 loop is fully preserved (LLM call, stop_reason check, message append — not a single word changed). The only change is in that one line of tool execution: `run_bash()` is replaced with `TOOL_HANDLERS[block.name]()` dispatch lookup.
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Adding a tool to the Agent requires just two things:
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1. **Define the tool**: Add one entry to the `TOOLS` array
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2. **Register the handler**: Add one mapping in the `TOOL_HANDLERS` dict
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---
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## From 1 Tool to 5 Tools
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s01 had only 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 expands to 5 tools, each independently defined:
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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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Each tool has its own implementation function:
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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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## Tool Dispatch
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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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# Only one line changed in the loop — from hardcoded run_bash to dispatch lookup:
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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] # lookup
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output = handler(**block.input) # call
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results.append(...)
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```
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Adding a tool = one entry in `TOOLS` array + one line in `TOOL_HANDLERS` dict. The loop stays the same.
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---
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## Multiple Tool Calls
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The model often returns multiple tool_use calls at once — "read a.py and b.py, then list all .py files".
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The teaching version executes them one by one in the original `response.content` order. CC's approach is more complex: it slices the original order into consecutive batches, where concurrency-safe tools within a batch run in parallel, and batches are strictly sequential (see appendix).
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---
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## Quick Reference
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| Concept | One-Liner |
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|---------|-----------|
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| TOOL_HANDLERS | Tool name → handler function dict. Add a tool = add one mapping line |
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| Tool Definition | JSON schema telling the model "what I can do" |
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| Multiple tool calls | Model may return multiple tool_use at once; teaching version executes them in original order |
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| Loop Unchanged | s01's `while True` loop — not a single line changed |
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---
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## Changes from s01
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| Component | Before (s01) | After (s02) |
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|-----------|-------------|-------------|
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| Tool count | 1 (bash) | 5 (+read, write, edit, glob) |
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| Tool execution | Hardcoded `run_bash()` | TOOL_HANDLERS dispatch lookup |
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| Path safety | None | safe_path validation (file tools only) |
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| Loop | `while True` + `stop_reason` | Identical to s01 |
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---
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## Try It
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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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Try these prompts:
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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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What to watch for: When does the model call just one tool, and when does it call multiple at once? Are multiple tool calls executed in the correct order?
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---
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## What's Next
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The Agent now has 5 specialized tools. File tools are protected by `safe_path`, but bash is unrestricted — `rm -rf /` still runs.
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→ s03 Permission: Add a gate before tool execution — is this operation safe? Does it need user approval?
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<details>
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<summary>Dive into CC Source Code</summary>
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> The following is based on a review of CC source code `Tool.ts`, `tools.ts`, `toolOrchestration.ts`, `toolExecution.ts`, and `StreamingToolExecutor.ts`.
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### 1. Tool Definition Approach
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**Teaching version**: `TOOLS` array + `TOOL_HANDLERS` dict. Definition and implementation are separate.
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**CC**: Each tool is an independent object created by `buildTool()`, containing schema, validation, permissions, and execution. `getAllBaseTools()` aggregates all tools.
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The teaching version's separation is clearer for teaching — readers immediately see "add a tool = two definitions".
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### 2. Concurrency Safety: isConcurrencySafe()
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The teaching version executes tools one by one in original order, without concurrency. CC uses `isConcurrencySafe(input)` to determine concurrency — note this isn't simply "read-only vs write", but judges by specific input:
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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** ← key difference |
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| Bash `rm` | false | false |
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| TaskCreate | false | **true** ← modifies state but can be concurrent (introduced in s12) |
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CC's Bash tool's `isConcurrencySafe` equals `isReadOnly` — read-only commands can be concurrent, write commands cannot. TaskCreate modifies task files, but each writes a different file, so it can be concurrent.
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### 3. Partition Algorithm
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CC's `partitionToolCalls()` (`toolOrchestration.ts:91-115`) doesn't split into two groups — it batches tool calls **by consecutive blocks**:
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```
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[read A, read B, glob *.py, bash "rm x", read C]
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→ batch1(concurrent): [read A, read B, glob *.py]
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→ batch2(serial): [bash "rm x"]
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→ batch3(concurrent): [read C]
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```
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Consecutive concurrency-safe calls are grouped into the same batch for truly concurrent execution (`toolOrchestration.ts:152-176`, with a concurrency limit). When a non-concurrency-safe call is encountered, a new batch starts for serial execution. Batches are strictly sequential.
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### 4. Validation Pipeline
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Each tool call in CC goes through a strict 5-step validation (`toolExecution.ts`):
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1. **Zod schema validation** (`614-680`, teaching version uses JSON Schema): parameter type/structure check
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2. **Tool-level validateInput()** (`682-733`): parameter value validation (e.g., is the path within the working directory)
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3. **PreToolUse hooks** (`800-862`, covered in s04): hooks can return messages, modify input, or block execution
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4. **Permission check** (`921-931`, core topic of s03): canUseTool + checkPermissions → allow/deny/ask
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5. **Execute tool.call()** (`1207-1222`)
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The teaching version omits Zod (uses JSON Schema), omits validateInput (uses safety functions), but preserves the permission check and hook concepts.
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### 5. Streaming Tool Execution
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CC's `StreamingToolExecutor` (`StreamingToolExecutor.ts`) starts tools while the model is still generating — no waiting for the model to finish. `read_file` might complete while the model is still outputting "Let me analyze". The teaching version doesn't implement this, consistent with s01's goal — conceptual clarity, not peak performance.
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### 6. Tool Result Persistence
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Each tool has a `maxResultSizeChars` field. Results exceeding this threshold are persisted to disk, and the model sees a preview + file path. FileRead is special — set to `Infinity`, preventing file read output from being persisted again. Specifically, if FileRead's result exceeds the threshold and gets persisted, the model's next read of that persisted file would trigger another persistence → infinite loop (read file → persist → re-read → re-persist → ...).
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</details>
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<!-- translation-sync: zh@v1, en@v1, ja@v1 -->
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