* 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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s04: Hooks — Hang on the Loop, Don't Write into It
s01 → s02 → s03 → s04 → s05 → s06 → ... → s20
"Hang on the loop, don't write into it" — Hooks inject extension logic before and after tool execution.
Harness Layer: Hooks — Extension points that don't invade the loop.
The Problem
The s03 Agent has permission checks. But every new check, "log every bash call", "auto git add after writes", requires modifying the agent_loop function.
The loop quickly becomes this:
def agent_loop(messages):
while True:
# ... LLM call ...
for block in response.content:
if block.type == "tool_use":
log_to_file(block) # added a line
check_permission(block) # added a line
notify_slack(block) # added another line
output = execute(block)
auto_git_add(block) # yet another line
# ... the loop is unrecognizable
What you want to extend is the Agent's behavior, but what you're modifying is the loop itself. The loop should be a stable core; extensions should hang on the outside.
The Solution
The s03 loop and permission logic are fully preserved. The only change is moving check_permission() from inside the loop body onto a hook. The loop no longer directly calls any check function. Instead it calls trigger_hooks("PreToolUse", block), and the registry decides what to run.
Four events, covering a complete agent cycle:
| Event | Trigger Timing | Typical Use |
|---|---|---|
| UserPromptSubmit | After user input, before entering LLM | Input validation, context injection |
| PreToolUse | Before tool execution | Permission checks, logging |
| PostToolUse | After tool execution | Side effects (auto git add etc.), output checking |
| Stop | When the loop is about to exit | Cleanup (CC also supports force continuation) |
Extensions are added via register_hook(). The loop only calls trigger_hooks().
How It Works
Hook registry: a dict mapping event names to callback lists.
HOOKS = {
"UserPromptSubmit": [],
"PreToolUse": [],
"PostToolUse": [],
"Stop": [],
}
def register_hook(event: str, callback):
HOOKS[event].append(callback)
def trigger_hooks(event: str, *args):
for callback in HOOKS[event]:
result = callback(*args)
if result is not None: # return value ≠ None → hook says "stop"
return result
return None
In the teaching version, PreToolUse returning non-None means block execution; Stop returning non-None means force continuation. UserPromptSubmit and PostToolUse return values are unused.
UserPromptSubmit, triggers after user input, before entering the LLM. CC can intercept or modify input; the teaching version only logs:
def context_inject_hook(query: str) -> str | None:
"""Inject current working directory info into every prompt."""
print(f"\033[90m[HOOK] UserPromptSubmit: working in {WORKDIR}\033[0m")
return None # return None = no modification, let prompt through
register_hook("UserPromptSubmit", context_inject_hook)
In the main loop, triggered right after user input:
query = input("s04 >> ")
trigger_hooks("UserPromptSubmit", query) # ← before entering LLM
history.append({"role": "user", "content": query})
agent_loop(history)
PreToolUse / PostToolUse, hooks before and after tool execution. s03's permission check logic is now wrapped as a PreToolUse hook, plus a logging hook and a large-output reminder:
# PreToolUse: permission check (s03 logic, moved from loop to hook)
def permission_hook(block):
if block.name == "bash":
for pattern in DENY_LIST:
if pattern in block.input.get("command", ""):
return "Permission denied by deny list"
if block.name in ("write_file", "edit_file"):
path = block.input.get("path", "")
if not (WORKDIR / path).resolve().is_relative_to(WORKDIR):
choice = input(" Allow? [y/N] ").strip().lower()
if choice not in ("y", "yes"):
return "Permission denied by user"
return None
# PreToolUse: logging
def log_hook(block):
print(f"[HOOK] {block.name}(...)")
# PostToolUse: large output reminder
def large_output_hook(block, output):
if len(str(output)) > 100000:
print(f"[HOOK] ⚠ Large output from {block.name}")
register_hook("PreToolUse", permission_hook)
register_hook("PreToolUse", log_hook)
register_hook("PostToolUse", large_output_hook)
Stop, triggers when the loop is about to exit (stop_reason != "tool_use"). The teaching version prints a cleanup summary:
def summary_hook(messages: list) -> str | None:
"""Print a summary when the loop is about to stop."""
tool_count = sum(1 for m in messages
for b in (m.get("content") if isinstance(m.get("content"), list) else [])
if isinstance(b, dict) and b.get("type") == "tool_result")
print(f"\033[90m[HOOK] Stop: session used {tool_count} tool calls\033[0m")
return None # return None = allow stop, return string = force continuation
register_hook("Stop", summary_hook)
In agent_loop, triggered before exit:
if response.stop_reason != "tool_use":
force = trigger_hooks("Stop", messages) # ← before exiting
if force:
# hook returned a message → inject it and continue
messages.append({"role": "user", "content": force})
continue
return
Only one change in the loop: s03 directly called check_permission(block), s04 replaces it with trigger_hooks("PreToolUse", block):
for block in response.content:
if block.type != "tool_use":
continue
# s03: if not check_permission(block): ...
# s04: hooks replace hardcoding
blocked = trigger_hooks("PreToolUse", block)
if blocked:
results.append({"type": "tool_result", "tool_use_id": block.id,
"content": str(blocked)})
continue
handler = TOOL_HANDLERS.get(block.name)
output = handler(**block.input) if handler else f"Unknown: {block.name}"
trigger_hooks("PostToolUse", block, output)
results.append({"type": "tool_result", "tool_use_id": block.id,
"content": output})
Four hooks cover the critical nodes of the agent cycle: input → before execution → after execution → exit. The loop only calls trigger_hooks(); all logic lives in hook callbacks.
Changes from s03
| Component | Before (s03) | After (s04) |
|---|---|---|
| Extension method | check_permission() hardcoded in the loop | HOOKS registry + trigger_hooks() |
| New functions | — | register_hook, trigger_hooks |
| Hook callbacks | — | context_inject_hook, permission_hook, log_hook, large_output_hook, summary_hook |
| Loop | Directly calls check_permission() | Calls trigger_hooks("PreToolUse", ...) |
| Exit control | None | trigger_hooks("Stop", ...) can prevent exit |
| Input interception | None | trigger_hooks("UserPromptSubmit", ...) can inject context |
Try It
cd learn-claude-code
python s04_hooks/code.py
Try these prompts:
Read the file README.md(should pass directly, observe hook logs)Create a file called test.txt(after creation, observe if PostToolUse fires)Delete all temporary files in /tmp(bash + rm triggers permission hook)
What to watch for: Before each tool execution, does the [HOOK] log appear? When permission is denied, was it intercepted by a hook or hardcoded in the loop?
What's Next
The Agent can now safely execute operations. But does it ever stop to think "what should I do first, and what next?" Given a complex task, does it jump straight in, or plan first?
→ s05 TodoWrite: Give the Agent a planning tool. Make a list first, then execute.
Dive into CC Source Code
The following is based on a complete analysis of CC source code
toolHooks.ts(650 lines),hooks.ts,stopHooks.ts, andcoreTypes.ts.
1. Hook Events: Not Just 4, but 27
The teaching version covers only PreToolUse and PostToolUse. CC actually has 27 hook events (coreTypes.ts:25-53):
| Category | Events |
|---|---|
| Tool-related | PreToolUse, PostToolUse, PostToolUseFailure |
| Session-related | SessionStart, SessionEnd, Stop, StopFailure, Setup |
| User interaction | UserPromptSubmit, Notification, PermissionRequest, PermissionDenied |
| Sub-agents | SubagentStart, SubagentStop |
| Compaction-related | PreCompact, PostCompact |
| Team-related | TeammateIdle, TaskCreated, TaskCompleted |
| Other | Elicitation, ElicitationResult, ConfigChange, WorktreeCreate, WorktreeRemove, InstructionsLoaded, CwdChanged, FileChanged |
The teaching version covers only 4 core events (UserPromptSubmit, PreToolUse, PostToolUse, Stop) because they cover every critical node of a complete agent cycle. The other 23 follow the same pattern.
2. HookResult Common Fields
CC's HookResult (types/hooks.ts:260-275) has 14 fields. Common ones:
| Field | Type | Purpose |
|---|---|---|
message |
Message | Optional UI message |
blockingError |
HookBlockingError | Blocking error → injected into conversation for model self-correction |
outcome |
success/blocking/non_blocking_error/cancelled | Execution result |
preventContinuation |
boolean | Prevent subsequent execution |
stopReason |
string | Stop reason description |
permissionBehavior |
allow/deny/ask/passthrough | Hook returns permission decision |
updatedInput |
Record | Modify tool input |
additionalContext |
string | Additional context |
updatedMCPToolOutput |
unknown | MCP tool output modification |
3. Key Invariant: Hook 'allow' Cannot Bypass deny/ask Rules
This is the most important security design in CC's permission system (toolHooks.ts:325-331): when a hook returns allow, it still checks settings.json deny/ask rules. Even if the user's hook script says "allow", if the tool is disabled in settings.json, the operation is still blocked.
The teaching version doesn't have this layer; hooks returning non-None directly interrupt. This is sufficient for teaching, but would create a security vulnerability in production.
4. stopHookActive Mechanism
CC's Stop hooks have an infinite-loop prevention mechanism (query.ts:212,1300): the stopHookActive state field. When stop hooks produce a blockingError, the loop re-enters with stopHookActive: true. Subsequent iterations see this flag and don't trigger stop hooks again. This prevents a never-stopping bug: model self-corrects → stop hook errors again → model self-corrects again → stop hook errors again...
5. hook_stopped_continuation
When PostToolUse hooks return preventContinuation: true, a hook_stopped_continuation attachment is produced (toolHooks.ts:117-130). query.ts (L1388-1393) detects it and sets shouldPreventContinuation = true, causing the loop to exit. This is the mechanism for "hooks gracefully shut down the Agent" — not a crash, but a completion.
Teaching Version Simplifications Are Intentional
- 27 events → 4 (UserPromptSubmit/PreToolUse/PostToolUse/Stop): covers agent cycle critical nodes
- 14 fields → simple return values (None = continue, non-None = interrupt/continue): minimal cognitive load
- Hook allow vs deny/ask invariant → omitted: teaching version has no settings.json layer
- stopHookActive → omitted: teaching version Stop hook only does simple continuation, no infinite-loop prevention needed