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                    THE AGENT PATTERN
                    =================

    User --> messages[] --> LLM --> response
                                      |
                            stop_reason == "tool_use"?
                           /                          \
                         yes                           no
                          |                             |
                    execute tools                    return text
                    append results
                    loop back -----------------> messages[]


    这是最小循环。每个 AI 编程 Agent 都需要这个循环。
    生产级 Agent 还会叠加策略、权限与生命周期层。

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def agent_loop(messages):
    while True:
        response = client.messages.create(
            model=MODEL, system=SYSTEM,
            messages=messages, tools=TOOLS,
        )
        messages.append({"role": "assistant",
                         "content": response.content})

        if response.stop_reason != "tool_use":
            return

        results = []
        for block in response.content:
            if block.type == "tool_use":
                output = TOOL_HANDLERS[block.name](**block.input)
                results.append({
                    "type": "tool_result",
                    "tool_use_id": block.id,
                    "content": output,
                })
        messages.append({"role": "user", "content": results})

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git clone https://github.com/shareAI-lab/learn-claude-code
cd learn-claude-code
pip install -r requirements.txt
cp .env.example .env   # 编辑 .env 填入你的 ANTHROPIC_API_KEY

python agents/s01_agent_loop.py       # 从这里开始
python agents/s12_worktree_task_isolation.py  # 完整递进终点
python agents/s_full.py               # 总纲: 全部机制合一

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cd web && npm install && npm run dev   # http://localhost:3000

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第一阶段: 循环                       第二阶段: 规划与知识
==================                   ==============================
s01  Agent 循环              [1]     s03  TodoWrite               [5]
     while + stop_reason                  TodoManager + nag 提醒
     |                                    |
     +-> s02  Tool Use            [4]     s04  子智能体             [5]
              dispatch map: name->handler     每个子智能体独立 messages[]
                                              |
                                         s05  Skills               [5]
                                              SKILL.md 通过 tool_result 注入
                                              |
                                         s06  Context Compact      [5]
                                              三层上下文压缩

第三阶段: 持久化                     第四阶段: 团队
==================                   =====================
s07  任务系统                [8]     s09  智能体团队             [9]
     文件持久化 CRUD + 依赖图             队友 + JSONL 邮箱
     |                                    |
s08  后台任务                [6]     s10  团队协议               [12]
     守护线程 + 通知队列                  关机 + 计划审批 FSM
                                          |
                                     s11  自治智能体             [14]
                                          空闲轮询 + 自动认领
                                     |
                                     s12  Worktree 隔离          [16]
                                          任务协调 + 按需隔离执行通道

                                     [N] = 工具数量

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learn-claude-code/
|
|-- agents/                        # Python 参考实现 (s01-s12 + s_full 总纲)
|-- docs/{en,zh,ja}/               # 心智模型优先的文档 (3 种语言)
|-- web/                           # 交互式学习平台 (Next.js)
|-- skills/                        # s05 的 Skill 文件
+-- .github/workflows/ci.yml      # CI: 类型检查 + 构建

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claw agent = agent core + heartbeat + cron + IM chat + memory + soul

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learn-claude-code                   claw0
(agent 运行时内核:                   (主动式常驻 AI 助手:
 循环、工具、规划、                    心跳、定时任务、IM 通道、
 团队、worktree 隔离)                  记忆、Soul 人格)

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export ANTHROPIC_API_KEY="your-api-key-here"
export ANTHROPIC_BASE_URL="your-anthropic-compatible-api-base-url"
export ANTHROPIC_MODEL="model-name"

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npx -y @scipen/mini-claude-code

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npm install -g @scipen/mini-claude-code

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git clone https://github.com/scipenai/mini-claude-code.git
cd mini-claude-code
npm install

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export ANTHROPIC_API_KEY="your-api-key-here"
export ANTHROPIC_BASE_URL="your-anthropic-compatable-api-base-url"
export ANTHROPIC_MODEL="model-name"

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npm install

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npm run build

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npm run dev

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npm run build
npm start

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┌──────────────────────────────────────────────────────────────────────────────┐
│ 🔌 MCP: 2 │ 🟢 Context: 45% │ 💬 Msgs: 67 │ 🎯 Skills: 3 │ 🤖 Agents: 2      │
└──────────────────────────────────────────────────────────────────────────────┘

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mkdir -p .mini-cc/skills/my-skill

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cat > .mini-cc/skills/my-skill/SKILL.md << 'EOF'
---
name: my-skill
description: Description of what this skill does
---

# My Skill

## Instructions

[Your skill instructions here...]
EOF

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/skills list              # 列出所有可用技能
/skills read my-skill     # 读取技能内容

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cp .mcp.example.json .mcp.json

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{
  "mcpServers": [
    {
      "name": "filesystem",
      "transport": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "/path/to/directory"
      ]
    },
    {
      "name": "remote-service",
      "transport": "streamable_http",
      "url": "https://your-mcp-server.example.com/mcp"
    }
  ]
}

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User: 创建一个名为 hello.js 的新文件，打印 "Hello, World!"
Assistant: 我将创建一个名为 hello.js 的新文件，打印 "Hello, World!"。

Tool: write_file
{
  "path": "hello.js",
  "content": "console.log('Hello, World!');\n"
}

Result: wrote 26 bytes to hello.js

我已经创建了 hello.js 文件，其中包含一个简单的程序，在控制台打印 "Hello, World!"。您可以使用 `node hello.js` 运行它。

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# 仅更新版本号
npm run version:patch  # 0.5.0 -> 0.5.1
npm run version:minor  # 0.5.1 -> 0.6.0
npm run version:major  # 0.5.1 -> 1.0.0

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#!/usr/bin/env python3
"""
s01_agent_loop.py - The Agent Loop

The entire secret of an AI coding agent in one pattern:

    while stop_reason == "tool_use":
        response = LLM(messages, tools)
        execute tools
        append results

    +----------+      +-------+      +---------+
    |   User   | ---> |  LLM  | ---> |  Tool   |
    |  prompt  |      |       |      | execute |
    +----------+      +---+---+      +----+----+
                          ^               |
                          |   tool_result |
                          +---------------+
                          (loop continues)

This is the core loop: feed tool results back to the model
until the model decides to stop. Production agents layer
policy, hooks, and lifecycle controls on top.
"""

import os
import subprocess

from anthropic import Anthropic
from dotenv import load_dotenv

load_dotenv(override=True)

if os.getenv("ANTHROPIC_BASE_URL"):
    os.environ.pop("ANTHROPIC_AUTH_TOKEN", None)

client = Anthropic(base_url=os.getenv("ANTHROPIC_BASE_URL"))
MODEL = os.environ["MODEL_ID"]

SYSTEM = f"You are a coding agent at {os.getcwd()}. Use bash to solve tasks. Act, don't explain."

TOOLS = [{
    "name": "bash",
    "description": "Run a shell command.",
    "input_schema": {
        "type": "object",
        "properties": {"command": {"type": "string"}},
        "required": ["command"],
    },
}]


def run_bash(command: str) -> str:
    dangerous = ["rm -rf /", "sudo", "shutdown", "reboot", "> /dev/"]
    if any(d in command for d in dangerous):
        return "Error: Dangerous command blocked"
    try:
        r = subprocess.run(command, shell=True, cwd=os.getcwd(),
                           capture_output=True, text=True, timeout=120)
        out = (r.stdout + r.stderr).strip()
        return out[:50000] if out else "(no output)"
    except subprocess.TimeoutExpired:
        return "Error: Timeout (120s)"


# -- The core pattern: a while loop that calls tools until the model stops --
def agent_loop(messages: list):
    while True:
        response = client.messages.create(
            model=MODEL, system=SYSTEM, messages=messages,
            tools=TOOLS, max_tokens=8000,
        )
        # Append assistant turn
        messages.append({"role": "assistant", "content": response.content})
        # If the model didn't call a tool, we're done
        if response.stop_reason != "tool_use":
            return
        # Execute each tool call, collect results
        results = []
        for block in response.content:
            if block.type == "tool_use":
                print(f"\033[33m$ {block.input['command']}\033[0m")
                output = run_bash(block.input["command"])
                print(output[:200])
                results.append({"type": "tool_result", "tool_use_id": block.id,
                                "content": output})
        messages.append({"role": "user", "content": results})


if __name__ == "__main__":
    history = []
    while True:
        try:
            query = input("\033[36ms01 >> \033[0m")
        except (EOFError, KeyboardInterrupt):
            break
        if query.strip().lower() in ("q", "exit", ""):
            break
        history.append({"role": "user", "content": query})
        agent_loop(history)
        response_content = history[-1]["content"]
        if isinstance(response_content, list):
            for block in response_content:
                if hasattr(block, "text"):
                    print(block.text)
        print()

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#!/usr/bin/env python3
"""
s02_tool_use.py - Tools

The agent loop from s01 didn't change. We just added tools to the array
and a dispatch map to route calls.

    +----------+      +-------+      +------------------+
    |   User   | ---> |  LLM  | ---> | Tool Dispatch    |
    |  prompt  |      |       |      | {                |
    +----------+      +---+---+      |   bash: run_bash |
                          ^          |   read: run_read |
                          |          |   write: run_wr  |
                          +----------+   edit: run_edit |
                          tool_result| }                |
                                     +------------------+

Key insight: "The loop didn't change at all. I just added tools."
"""

import os
import subprocess
from pathlib import Path

from anthropic import Anthropic
from dotenv import load_dotenv

load_dotenv(override=True)

if os.getenv("ANTHROPIC_BASE_URL"):
    os.environ.pop("ANTHROPIC_AUTH_TOKEN", None)

WORKDIR = Path.cwd()
client = Anthropic(base_url=os.getenv("ANTHROPIC_BASE_URL"))
MODEL = os.environ["MODEL_ID"]

SYSTEM = f"You are a coding agent at {WORKDIR}. Use tools to solve tasks. Act, don't explain."


def safe_path(p: str) -> Path:
    path = (WORKDIR / p).resolve()
    if not path.is_relative_to(WORKDIR):
        raise ValueError(f"Path escapes workspace: {p}")
    return path


def run_bash(command: str) -> str:
    dangerous = ["rm -rf /", "sudo", "shutdown", "reboot", "> /dev/"]
    if any(d in command for d in dangerous):
        return "Error: Dangerous command blocked"
    try:
        r = subprocess.run(command, shell=True, cwd=WORKDIR,
                           capture_output=True, text=True, timeout=120)
        out = (r.stdout + r.stderr).strip()
        return out[:50000] if out else "(no output)"
    except subprocess.TimeoutExpired:
        return "Error: Timeout (120s)"


def run_read(path: str, limit: int = None) -> str:
    try:
        text = safe_path(path).read_text()
        lines = text.splitlines()
        if limit and limit < len(lines):
            lines = lines[:limit] + [f"... ({len(lines) - limit} more lines)"]
        return "\n".join(lines)[:50000]
    except Exception as e:
        return f"Error: {e}"


def run_write(path: str, content: str) -> str:
    try:
        fp = safe_path(path)
        fp.parent.mkdir(parents=True, exist_ok=True)
        fp.write_text(content)
        return f"Wrote {len(content)} bytes to {path}"
    except Exception as e:
        return f"Error: {e}"


def run_edit(path: str, old_text: str, new_text: str) -> str:
    try:
        fp = safe_path(path)
        content = fp.read_text()
        if old_text not in content:
            return f"Error: Text not found in {path}"
        fp.write_text(content.replace(old_text, new_text, 1))
        return f"Edited {path}"
    except Exception as e:
        return f"Error: {e}"


# -- The dispatch map: {tool_name: handler} --
TOOL_HANDLERS = {
    "bash":       lambda **kw: run_bash(kw["command"]),
    "read_file":  lambda **kw: run_read(kw["path"], kw.get("limit")),
    "write_file": lambda **kw: run_write(kw["path"], kw["content"]),
    "edit_file":  lambda **kw: run_edit(kw["path"], kw["old_text"], kw["new_text"]),
}

TOOLS = [
    {"name": "bash", "description": "Run a shell command.",
     "input_schema": {"type": "object", "properties": {"command": {"type": "string"}}, "required": ["command"]}},
    {"name": "read_file", "description": "Read file contents.",
     "input_schema": {"type": "object", "properties": {"path": {"type": "string"}, "limit": {"type": "integer"}}, "required": ["path"]}},
    {"name": "write_file", "description": "Write content to file.",
     "input_schema": {"type": "object", "properties": {"path": {"type": "string"}, "content": {"type": "string"}}, "required": ["path", "content"]}},
    {"name": "edit_file", "description": "Replace exact text in file.",
     "input_schema": {"type": "object", "properties": {"path": {"type": "string"}, "old_text": {"type": "string"}, "new_text": {"type": "string"}}, "required": ["path", "old_text", "new_text"]}},
]


def agent_loop(messages: list):
    while True:
        response = client.messages.create(
            model=MODEL, system=SYSTEM, messages=messages,
            tools=TOOLS, max_tokens=8000,
        )
        messages.append({"role": "assistant", "content": response.content})
        if response.stop_reason != "tool_use":
            return
        results = []
        for block in response.content:
            if block.type == "tool_use":
                handler = TOOL_HANDLERS.get(block.name)
                output = handler(**block.input) if handler else f"Unknown tool: {block.name}"
                print(f"> {block.name}: {output[:200]}")
                results.append({"type": "tool_result", "tool_use_id": block.id, "content": output})
        messages.append({"role": "user", "content": results})


if __name__ == "__main__":
    history = []
    while True:
        try:
            query = input("\033[36ms02 >> \033[0m")
        except (EOFError, KeyboardInterrupt):
            break
        if query.strip().lower() in ("q", "exit", ""):
            break
        history.append({"role": "user", "content": query})
        agent_loop(history)
        response_content = history[-1]["content"]
        if isinstance(response_content, list):
            for block in response_content:
                if hasattr(block, "text"):
                    print(block.text)
        print()

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#!/usr/bin/env python3
"""
s_full.py - Full Reference Agent

Capstone implementation combining every mechanism from s01-s11.
Session s12 (task-aware worktree isolation) is taught separately.
NOT a teaching session -- this is the "put it all together" reference.

    +------------------------------------------------------------------+
    |                        FULL AGENT                                 |
    |                                                                   |
    |  System prompt (s05 skills, task-first + optional todo nag)      |
    |                                                                   |
    |  Before each LLM call:                                            |
    |  +--------------------+  +------------------+  +--------------+  |
    |  | Microcompact (s06) |  | Drain bg (s08)   |  | Check inbox  |  |
    |  | Auto-compact (s06) |  | notifications    |  | (s09)        |  |
    |  +--------------------+  +------------------+  +--------------+  |
    |                                                                   |
    |  Tool dispatch (s02 pattern):                                     |
    |  +--------+----------+----------+---------+-----------+          |
    |  | bash   | read     | write    | edit    | TodoWrite |          |
    |  | task   | load_sk  | compress | bg_run  | bg_check  |          |
    |  | t_crt  | t_get    | t_upd    | t_list  | spawn_tm  |          |
    |  | list_tm| send_msg | rd_inbox | bcast   | shutdown  |          |
    |  | plan   | idle     | claim    |         |           |          |
    |  +--------+----------+----------+---------+-----------+          |
    |                                                                   |
    |  Subagent (s04):  spawn -> work -> return summary                 |
    |  Teammate (s09):  spawn -> work -> idle -> auto-claim (s11)      |
    |  Shutdown (s10):  request_id handshake                            |
    |  Plan gate (s10): submit -> approve/reject                        |
    +------------------------------------------------------------------+

    REPL commands: /compact /tasks /team /inbox
"""

import json
import os
import re
import subprocess
import threading
import time
import uuid
from pathlib import Path
from queue import Queue

from anthropic import Anthropic
from dotenv import load_dotenv

load_dotenv(override=True)
if os.getenv("ANTHROPIC_BASE_URL"):
    os.environ.pop("ANTHROPIC_AUTH_TOKEN", None)

WORKDIR = Path.cwd()
client = Anthropic(base_url=os.getenv("ANTHROPIC_BASE_URL"))
MODEL = os.environ["MODEL_ID"]

TEAM_DIR = WORKDIR / ".team"
INBOX_DIR = TEAM_DIR / "inbox"
TASKS_DIR = WORKDIR / ".tasks"
SKILLS_DIR = WORKDIR / "skills"
TRANSCRIPT_DIR = WORKDIR / ".transcripts"
TOKEN_THRESHOLD = 100000
POLL_INTERVAL = 5
IDLE_TIMEOUT = 60

VALID_MSG_TYPES = {"message", "broadcast", "shutdown_request",
                   "shutdown_response", "plan_approval_response"}


# === SECTION: base_tools ===
def safe_path(p: str) -> Path:
    path = (WORKDIR / p).resolve()
    if not path.is_relative_to(WORKDIR):
        raise ValueError(f"Path escapes workspace: {p}")
    return path

def run_bash(command: str) -> str:
    dangerous = ["rm -rf /", "sudo", "shutdown", "reboot", "> /dev/"]
    if any(d in command for d in dangerous):
        return "Error: Dangerous command blocked"
    try:
        r = subprocess.run(command, shell=True, cwd=WORKDIR,
                           capture_output=True, text=True, timeout=120)
        out = (r.stdout + r.stderr).strip()
        return out[:50000] if out else "(no output)"
    except subprocess.TimeoutExpired:
        return "Error: Timeout (120s)"

def run_read(path: str, limit: int = None) -> str:
    try:
        lines = safe_path(path).read_text().splitlines()
        if limit and limit < len(lines):
            lines = lines[:limit] + [f"... ({len(lines) - limit} more)"]
        return "\n".join(lines)[:50000]
    except Exception as e:
        return f"Error: {e}"

def run_write(path: str, content: str) -> str:
    try:
        fp = safe_path(path)
        fp.parent.mkdir(parents=True, exist_ok=True)
        fp.write_text(content)
        return f"Wrote {len(content)} bytes to {path}"
    except Exception as e:
        return f"Error: {e}"

def run_edit(path: str, old_text: str, new_text: str) -> str:
    try:
        fp = safe_path(path)
        c = fp.read_text()
        if old_text not in c:
            return f"Error: Text not found in {path}"
        fp.write_text(c.replace(old_text, new_text, 1))
        return f"Edited {path}"
    except Exception as e:
        return f"Error: {e}"


# === SECTION: todos (s03) ===
class TodoManager:
    def __init__(self):
        self.items = []

    def update(self, items: list) -> str:
        validated, ip = [], 0
        for i, item in enumerate(items):
            content = str(item.get("content", "")).strip()
            status = str(item.get("status", "pending")).lower()
            af = str(item.get("activeForm", "")).strip()
            if not content: raise ValueError(f"Item {i}: content required")
            if status not in ("pending", "in_progress", "completed"):
                raise ValueError(f"Item {i}: invalid status '{status}'")
            if not af: raise ValueError(f"Item {i}: activeForm required")
            if status == "in_progress": ip += 1
            validated.append({"content": content, "status": status, "activeForm": af})
        if len(validated) > 20: raise ValueError("Max 20 todos")
        if ip > 1: raise ValueError("Only one in_progress allowed")
        self.items = validated
        return self.render()

    def render(self) -> str:
        if not self.items: return "No todos."
        lines = []
        for item in self.items:
            m = {"completed": "[x]", "in_progress": "[>]", "pending": "[ ]"}.get(item["status"], "[?]")
            suffix = f" <- {item['activeForm']}" if item["status"] == "in_progress" else ""
            lines.append(f"{m} {item['content']}{suffix}")
        done = sum(1 for t in self.items if t["status"] == "completed")
        lines.append(f"\n({done}/{len(self.items)} completed)")
        return "\n".join(lines)

    def has_open_items(self) -> bool:
        return any(item.get("status") != "completed" for item in self.items)


# === SECTION: subagent (s04) ===
def run_subagent(prompt: str, agent_type: str = "Explore") -> str:
    sub_tools = [
        {"name": "bash", "description": "Run command.",
         "input_schema": {"type": "object", "properties": {"command": {"type": "string"}}, "required": ["command"]}},
        {"name": "read_file", "description": "Read file.",
         "input_schema": {"type": "object", "properties": {"path": {"type": "string"}}, "required": ["path"]}},
    ]
    if agent_type != "Explore":
        sub_tools += [
            {"name": "write_file", "description": "Write file.",
             "input_schema": {"type": "object", "properties": {"path": {"type": "string"}, "content": {"type": "string"}}, "required": ["path", "content"]}},
            {"name": "edit_file", "description": "Edit file.",
             "input_schema": {"type": "object", "properties": {"path": {"type": "string"}, "old_text": {"type": "string"}, "new_text": {"type": "string"}}, "required": ["path", "old_text", "new_text"]}},
        ]
    sub_handlers = {
        "bash": lambda **kw: run_bash(kw["command"]),
        "read_file": lambda **kw: run_read(kw["path"]),
        "write_file": lambda **kw: run_write(kw["path"], kw["content"]),
        "edit_file": lambda **kw: run_edit(kw["path"], kw["old_text"], kw["new_text"]),
    }
    sub_msgs = [{"role": "user", "content": prompt}]
    resp = None
    for _ in range(30):
        resp = client.messages.create(model=MODEL, messages=sub_msgs, tools=sub_tools, max_tokens=8000)
        sub_msgs.append({"role": "assistant", "content": resp.content})
        if resp.stop_reason != "tool_use":
            break
        results = []
        for b in resp.content:
            if b.type == "tool_use":
                h = sub_handlers.get(b.name, lambda **kw: "Unknown tool")
                results.append({"type": "tool_result", "tool_use_id": b.id, "content": str(h(**b.input))[:50000]})
        sub_msgs.append({"role": "user", "content": results})
    if resp:
        return "".join(b.text for b in resp.content if hasattr(b, "text")) or "(no summary)"
    return "(subagent failed)"


# === SECTION: skills (s05) ===
class SkillLoader:
    def __init__(self, skills_dir: Path):
        self.skills = {}
        if skills_dir.exists():
            for f in sorted(skills_dir.rglob("SKILL.md")):
                text = f.read_text()
                match = re.match(r"^---\n(.*?)\n---\n(.*)", text, re.DOTALL)
                meta, body = {}, text
                if match:
                    for line in match.group(1).strip().splitlines():
                        if ":" in line:
                            k, v = line.split(":", 1)
                            meta[k.strip()] = v.strip()
                    body = match.group(2).strip()
                name = meta.get("name", f.parent.name)
                self.skills[name] = {"meta": meta, "body": body}

    def descriptions(self) -> str:
        if not self.skills: return "(no skills)"
        return "\n".join(f"  - {n}: {s['meta'].get('description', '-')}" for n, s in self.skills.items())

    def load(self, name: str) -> str:
        s = self.skills.get(name)
        if not s: return f"Error: Unknown skill '{name}'. Available: {', '.join(self.skills.keys())}"
        return f"<skill name=\"{name}\">\n{s['body']}\n</skill>"


# === SECTION: compression (s06) ===
def estimate_tokens(messages: list) -> int:
    return len(json.dumps(messages, default=str)) // 4

def microcompact(messages: list):
    indices = []
    for i, msg in enumerate(messages):
        if msg["role"] == "user" and isinstance(msg.get("content"), list):
            for part in msg["content"]:
                if isinstance(part, dict) and part.get("type") == "tool_result":
                    indices.append(part)
    if len(indices) <= 3:
        return
    for part in indices[:-3]:
        if isinstance(part.get("content"), str) and len(part["content"]) > 100:
            part["content"] = "[cleared]"

def auto_compact(messages: list) -> list:
    TRANSCRIPT_DIR.mkdir(exist_ok=True)
    path = TRANSCRIPT_DIR / f"transcript_{int(time.time())}.jsonl"
    with open(path, "w") as f:
        for msg in messages:
            f.write(json.dumps(msg, default=str) + "\n")
    conv_text = json.dumps(messages, default=str)[:80000]
    resp = client.messages.create(
        model=MODEL,
        messages=[{"role": "user", "content": f"Summarize for continuity:\n{conv_text}"}],
        max_tokens=2000,
    )
    summary = resp.content[0].text
    return [
        {"role": "user", "content": f"[Compressed. Transcript: {path}]\n{summary}"},
        {"role": "assistant", "content": "Understood. Continuing with summary context."},
    ]


# === SECTION: file_tasks (s07) ===
class TaskManager:
    def __init__(self):
        TASKS_DIR.mkdir(exist_ok=True)

    def _next_id(self) -> int:
        ids = [int(f.stem.split("_")[1]) for f in TASKS_DIR.glob("task_*.json")]
        return max(ids, default=0) + 1

    def _load(self, tid: int) -> dict:
        p = TASKS_DIR / f"task_{tid}.json"
        if not p.exists(): raise ValueError(f"Task {tid} not found")
        return json.loads(p.read_text())

    def _save(self, task: dict):
        (TASKS_DIR / f"task_{task['id']}.json").write_text(json.dumps(task, indent=2))

    def create(self, subject: str, description: str = "") -> str:
        task = {"id": self._next_id(), "subject": subject, "description": description,
                "status": "pending", "owner": None, "blockedBy": [], "blocks": []}
        self._save(task)
        return json.dumps(task, indent=2)

    def get(self, tid: int) -> str:
        return json.dumps(self._load(tid), indent=2)

    def update(self, tid: int, status: str = None,
               add_blocked_by: list = None, add_blocks: list = None) -> str:
        task = self._load(tid)
        if status:
            task["status"] = status
            if status == "completed":
                for f in TASKS_DIR.glob("task_*.json"):
                    t = json.loads(f.read_text())
                    if tid in t.get("blockedBy", []):
                        t["blockedBy"].remove(tid)
                        self._save(t)
            if status == "deleted":
                (TASKS_DIR / f"task_{tid}.json").unlink(missing_ok=True)
                return f"Task {tid} deleted"
        if add_blocked_by:
            task["blockedBy"] = list(set(task["blockedBy"] + add_blocked_by))
        if add_blocks:
            task["blocks"] = list(set(task["blocks"] + add_blocks))
        self._save(task)
        return json.dumps(task, indent=2)

    def list_all(self) -> str:
        tasks = [json.loads(f.read_text()) for f in sorted(TASKS_DIR.glob("task_*.json"))]
        if not tasks: return "No tasks."
        lines = []
        for t in tasks:
            m = {"pending": "[ ]", "in_progress": "[>]", "completed": "[x]"}.get(t["status"], "[?]")
            owner = f" @{t['owner']}" if t.get("owner") else ""
            blocked = f" (blocked by: {t['blockedBy']})" if t.get("blockedBy") else ""
            lines.append(f"{m} #{t['id']}: {t['subject']}{owner}{blocked}")
        return "\n".join(lines)

    def claim(self, tid: int, owner: str) -> str:
        task = self._load(tid)
        task["owner"] = owner
        task["status"] = "in_progress"
        self._save(task)
        return f"Claimed task #{tid} for {owner}"


# === SECTION: background (s08) ===
class BackgroundManager:
    def __init__(self):
        self.tasks = {}
        self.notifications = Queue()

    def run(self, command: str, timeout: int = 120) -> str:
        tid = str(uuid.uuid4())[:8]
        self.tasks[tid] = {"status": "running", "command": command, "result": None}
        threading.Thread(target=self._exec, args=(tid, command, timeout), daemon=True).start()
        return f"Background task {tid} started: {command[:80]}"

    def _exec(self, tid: str, command: str, timeout: int):
        try:
            r = subprocess.run(command, shell=True, cwd=WORKDIR,
                               capture_output=True, text=True, timeout=timeout)
            output = (r.stdout + r.stderr).strip()[:50000]
            self.tasks[tid].update({"status": "completed", "result": output or "(no output)"})
        except Exception as e:
            self.tasks[tid].update({"status": "error", "result": str(e)})
        self.notifications.put({"task_id": tid, "status": self.tasks[tid]["status"],
                                "result": self.tasks[tid]["result"][:500]})

    def check(self, tid: str = None) -> str:
        if tid:
            t = self.tasks.get(tid)
            return f"[{t['status']}] {t.get('result', '(running)')}" if t else f"Unknown: {tid}"
        return "\n".join(f"{k}: [{v['status']}] {v['command'][:60]}" for k, v in self.tasks.items()) or "No bg tasks."

    def drain(self) -> list:
        notifs = []
        while not self.notifications.empty():
            notifs.append(self.notifications.get_nowait())
        return notifs


# === SECTION: messaging (s09) ===
class MessageBus:
    def __init__(self):
        INBOX_DIR.mkdir(parents=True, exist_ok=True)

    def send(self, sender: str, to: str, content: str,
             msg_type: str = "message", extra: dict = None) -> str:
        msg = {"type": msg_type, "from": sender, "content": content,
               "timestamp": time.time()}
        if extra: msg.update(extra)
        with open(INBOX_DIR / f"{to}.jsonl", "a") as f:
            f.write(json.dumps(msg) + "\n")
        return f"Sent {msg_type} to {to}"

    def read_inbox(self, name: str) -> list:
        path = INBOX_DIR / f"{name}.jsonl"
        if not path.exists(): return []
        msgs = [json.loads(l) for l in path.read_text().strip().splitlines() if l]
        path.write_text("")
        return msgs

    def broadcast(self, sender: str, content: str, names: list) -> str:
        count = 0
        for n in names:
            if n != sender:
                self.send(sender, n, content, "broadcast")
                count += 1
        return f"Broadcast to {count} teammates"


# === SECTION: shutdown + plan tracking (s10) ===
shutdown_requests = {}
plan_requests = {}


# === SECTION: team (s09/s11) ===
class TeammateManager:
    def __init__(self, bus: MessageBus, task_mgr: TaskManager):
        TEAM_DIR.mkdir(exist_ok=True)
        self.bus = bus
        self.task_mgr = task_mgr
        self.config_path = TEAM_DIR / "config.json"
        self.config = self._load()
        self.threads = {}

    def _load(self) -> dict:
        if self.config_path.exists():
            return json.loads(self.config_path.read_text())
        return {"team_name": "default", "members": []}

    def _save(self):
        self.config_path.write_text(json.dumps(self.config, indent=2))

    def _find(self, name: str) -> dict:
        for m in self.config["members"]:
            if m["name"] == name: return m
        return None

    def spawn(self, name: str, role: str, prompt: str) -> str:
        member = self._find(name)
        if member:
            if member["status"] not in ("idle", "shutdown"):
                return f"Error: '{name}' is currently {member['status']}"
            member["status"] = "working"
            member["role"] = role
        else:
            member = {"name": name, "role": role, "status": "working"}
            self.config["members"].append(member)
        self._save()
        threading.Thread(target=self._loop, args=(name, role, prompt), daemon=True).start()
        return f"Spawned '{name}' (role: {role})"

    def _set_status(self, name: str, status: str):
        member = self._find(name)
        if member:
            member["status"] = status
            self._save()

    def _loop(self, name: str, role: str, prompt: str):
        team_name = self.config["team_name"]
        sys_prompt = (f"You are '{name}', role: {role}, team: {team_name}, at {WORKDIR}. "
                      f"Use idle when done with current work. You may auto-claim tasks.")
        messages = [{"role": "user", "content": prompt}]
        tools = [
            {"name": "bash", "description": "Run command.", "input_schema": {"type": "object", "properties": {"command": {"type": "string"}}, "required": ["command"]}},
            {"name": "read_file", "description": "Read file.", "input_schema": {"type": "object", "properties": {"path": {"type": "string"}}, "required": ["path"]}},
            {"name": "write_file", "description": "Write file.", "input_schema": {"type": "object", "properties": {"path": {"type": "string"}, "content": {"type": "string"}}, "required": ["path", "content"]}},
            {"name": "edit_file", "description": "Edit file.", "input_schema": {"type": "object", "properties": {"path": {"type": "string"}, "old_text": {"type": "string"}, "new_text": {"type": "string"}}, "required": ["path", "old_text", "new_text"]}},
            {"name": "send_message", "description": "Send message.", "input_schema": {"type": "object", "properties": {"to": {"type": "string"}, "content": {"type": "string"}}, "required": ["to", "content"]}},
            {"name": "idle", "description": "Signal no more work.", "input_schema": {"type": "object", "properties": {}}},
            {"name": "claim_task", "description": "Claim task by ID.", "input_schema": {"type": "object", "properties": {"task_id": {"type": "integer"}}, "required": ["task_id"]}},
        ]
        while True:
            # -- WORK PHASE --
            for _ in range(50):
                inbox = self.bus.read_inbox(name)
                for msg in inbox:
                    if msg.get("type") == "shutdown_request":
                        self._set_status(name, "shutdown")
                        return
                    messages.append({"role": "user", "content": json.dumps(msg)})
                try:
                    response = client.messages.create(
                        model=MODEL, system=sys_prompt, messages=messages,
                        tools=tools, max_tokens=8000)
                except Exception:
                    self._set_status(name, "shutdown")
                    return
                messages.append({"role": "assistant", "content": response.content})
                if response.stop_reason != "tool_use":
                    break
                results = []
                idle_requested = False
                for block in response.content:
                    if block.type == "tool_use":
                        if block.name == "idle":
                            idle_requested = True
                            output = "Entering idle phase."
                        elif block.name == "claim_task":
                            output = self.task_mgr.claim(block.input["task_id"], name)
                        elif block.name == "send_message":
                            output = self.bus.send(name, block.input["to"], block.input["content"])
                        else:
                            dispatch = {"bash": lambda **kw: run_bash(kw["command"]),
                                        "read_file": lambda **kw: run_read(kw["path"]),
                                        "write_file": lambda **kw: run_write(kw["path"], kw["content"]),
                                        "edit_file": lambda **kw: run_edit(kw["path"], kw["old_text"], kw["new_text"])}
                            output = dispatch.get(block.name, lambda **kw: "Unknown")(**block.input)
                        print(f"  [{name}] {block.name}: {str(output)[:120]}")
                        results.append({"type": "tool_result", "tool_use_id": block.id, "content": str(output)})
                messages.append({"role": "user", "content": results})
                if idle_requested:
                    break
            # -- IDLE PHASE: poll for messages and unclaimed tasks --
            self._set_status(name, "idle")
            resume = False
            for _ in range(IDLE_TIMEOUT // max(POLL_INTERVAL, 1)):
                time.sleep(POLL_INTERVAL)
                inbox = self.bus.read_inbox(name)
                if inbox:
                    for msg in inbox:
                        if msg.get("type") == "shutdown_request":
                            self._set_status(name, "shutdown")
                            return
                        messages.append({"role": "user", "content": json.dumps(msg)})
                    resume = True
                    break
                unclaimed = []
                for f in sorted(TASKS_DIR.glob("task_*.json")):
                    t = json.loads(f.read_text())
                    if t.get("status") == "pending" and not t.get("owner") and not t.get("blockedBy"):
                        unclaimed.append(t)
                if unclaimed:
                    task = unclaimed[0]
                    self.task_mgr.claim(task["id"], name)
                    # Identity re-injection for compressed contexts
                    if len(messages) <= 3:
                        messages.insert(0, {"role": "user", "content":
                            f"<identity>You are '{name}', role: {role}, team: {team_name}.</identity>"})
                        messages.insert(1, {"role": "assistant", "content": f"I am {name}. Continuing."})
                    messages.append({"role": "user", "content":
                        f"<auto-claimed>Task #{task['id']}: {task['subject']}\n{task.get('description', '')}</auto-claimed>"})
                    messages.append({"role": "assistant", "content": f"Claimed task #{task['id']}. Working on it."})
                    resume = True
                    break
            if not resume:
                self._set_status(name, "shutdown")
                return
            self._set_status(name, "working")

    def list_all(self) -> str:
        if not self.config["members"]: return "No teammates."
        lines = [f"Team: {self.config['team_name']}"]
        for m in self.config["members"]:
            lines.append(f"  {m['name']} ({m['role']}): {m['status']}")
        return "\n".join(lines)

    def member_names(self) -> list:
        return [m["name"] for m in self.config["members"]]


# === SECTION: global_instances ===
TODO = TodoManager()
SKILLS = SkillLoader(SKILLS_DIR)
TASK_MGR = TaskManager()
BG = BackgroundManager()
BUS = MessageBus()
TEAM = TeammateManager(BUS, TASK_MGR)

# === SECTION: system_prompt ===
SYSTEM = f"""You are a coding agent at {WORKDIR}. Use tools to solve tasks.
Prefer task_create/task_update/task_list for multi-step work. Use TodoWrite for short checklists.
Use task for subagent delegation. Use load_skill for specialized knowledge.
Skills: {SKILLS.descriptions()}"""


# === SECTION: shutdown_protocol (s10) ===
def handle_shutdown_request(teammate: str) -> str:
    req_id = str(uuid.uuid4())[:8]
    shutdown_requests[req_id] = {"target": teammate, "status": "pending"}
    BUS.send("lead", teammate, "Please shut down.", "shutdown_request", {"request_id": req_id})
    return f"Shutdown request {req_id} sent to '{teammate}'"

# === SECTION: plan_approval (s10) ===
def handle_plan_review(request_id: str, approve: bool, feedback: str = "") -> str:
    req = plan_requests.get(request_id)
    if not req: return f"Error: Unknown plan request_id '{request_id}'"
    req["status"] = "approved" if approve else "rejected"
    BUS.send("lead", req["from"], feedback, "plan_approval_response",
             {"request_id": request_id, "approve": approve, "feedback": feedback})
    return f"Plan {req['status']} for '{req['from']}'"


# === SECTION: tool_dispatch (s02) ===
TOOL_HANDLERS = {
    "bash":             lambda **kw: run_bash(kw["command"]),
    "read_file":        lambda **kw: run_read(kw["path"], kw.get("limit")),
    "write_file":       lambda **kw: run_write(kw["path"], kw["content"]),
    "edit_file":        lambda **kw: run_edit(kw["path"], kw["old_text"], kw["new_text"]),
    "TodoWrite":        lambda **kw: TODO.update(kw["items"]),
    "task":             lambda **kw: run_subagent(kw["prompt"], kw.get("agent_type", "Explore")),
    "load_skill":       lambda **kw: SKILLS.load(kw["name"]),
    "compress":         lambda **kw: "Compressing...",
    "background_run":   lambda **kw: BG.run(kw["command"], kw.get("timeout", 120)),
    "check_background": lambda **kw: BG.check(kw.get("task_id")),
    "task_create":      lambda **kw: TASK_MGR.create(kw["subject"], kw.get("description", "")),
    "task_get":         lambda **kw: TASK_MGR.get(kw["task_id"]),
    "task_update":      lambda **kw: TASK_MGR.update(kw["task_id"], kw.get("status"), kw.get("add_blocked_by"), kw.get("add_blocks")),
    "task_list":        lambda **kw: TASK_MGR.list_all(),
    "spawn_teammate":   lambda **kw: TEAM.spawn(kw["name"], kw["role"], kw["prompt"]),
    "list_teammates":   lambda **kw: TEAM.list_all(),
    "send_message":     lambda **kw: BUS.send("lead", kw["to"], kw["content"], kw.get("msg_type", "message")),
    "read_inbox":       lambda **kw: json.dumps(BUS.read_inbox("lead"), indent=2),
    "broadcast":        lambda **kw: BUS.broadcast("lead", kw["content"], TEAM.member_names()),
    "shutdown_request": lambda **kw: handle_shutdown_request(kw["teammate"]),
    "plan_approval":    lambda **kw: handle_plan_review(kw["request_id"], kw["approve"], kw.get("feedback", "")),
    "idle":             lambda **kw: "Lead does not idle.",
    "claim_task":       lambda **kw: TASK_MGR.claim(kw["task_id"], "lead"),
}

TOOLS = [
    {"name": "bash", "description": "Run a shell command.",
     "input_schema": {"type": "object", "properties": {"command": {"type": "string"}}, "required": ["command"]}},
    {"name": "read_file", "description": "Read file contents.",
     "input_schema": {"type": "object", "properties": {"path": {"type": "string"}, "limit": {"type": "integer"}}, "required": ["path"]}},
    {"name": "write_file", "description": "Write content to file.",
     "input_schema": {"type": "object", "properties": {"path": {"type": "string"}, "content": {"type": "string"}}, "required": ["path", "content"]}},
    {"name": "edit_file", "description": "Replace exact text in file.",
     "input_schema": {"type": "object", "properties": {"path": {"type": "string"}, "old_text": {"type": "string"}, "new_text": {"type": "string"}}, "required": ["path", "old_text", "new_text"]}},
    {"name": "TodoWrite", "description": "Update task tracking list.",
     "input_schema": {"type": "object", "properties": {"items": {"type": "array", "items": {"type": "object", "properties": {"content": {"type": "string"}, "status": {"type": "string", "enum": ["pending", "in_progress", "completed"]}, "activeForm": {"type": "string"}}, "required": ["content", "status", "activeForm"]}}}, "required": ["items"]}},
    {"name": "task", "description": "Spawn a subagent for isolated exploration or work.",
     "input_schema": {"type": "object", "properties": {"prompt": {"type": "string"}, "agent_type": {"type": "string", "enum": ["Explore", "general-purpose"]}}, "required": ["prompt"]}},
    {"name": "load_skill", "description": "Load specialized knowledge by name.",
     "input_schema": {"type": "object", "properties": {"name": {"type": "string"}}, "required": ["name"]}},
    {"name": "compress", "description": "Manually compress conversation context.",
     "input_schema": {"type": "object", "properties": {}}},
    {"name": "background_run", "description": "Run command in background thread.",
     "input_schema": {"type": "object", "properties": {"command": {"type": "string"}, "timeout": {"type": "integer"}}, "required": ["command"]}},
    {"name": "check_background", "description": "Check background task status.",
     "input_schema": {"type": "object", "properties": {"task_id": {"type": "string"}}}},
    {"name": "task_create", "description": "Create a persistent file task.",
     "input_schema": {"type": "object", "properties": {"subject": {"type": "string"}, "description": {"type": "string"}}, "required": ["subject"]}},
    {"name": "task_get", "description": "Get task details by ID.",
     "input_schema": {"type": "object", "properties": {"task_id": {"type": "integer"}}, "required": ["task_id"]}},
    {"name": "task_update", "description": "Update task status or dependencies.",
     "input_schema": {"type": "object", "properties": {"task_id": {"type": "integer"}, "status": {"type": "string", "enum": ["pending", "in_progress", "completed", "deleted"]}, "add_blocked_by": {"type": "array", "items": {"type": "integer"}}, "add_blocks": {"type": "array", "items": {"type": "integer"}}}, "required": ["task_id"]}},
    {"name": "task_list", "description": "List all tasks.",
     "input_schema": {"type": "object", "properties": {}}},
    {"name": "spawn_teammate", "description": "Spawn a persistent autonomous teammate.",
     "input_schema": {"type": "object", "properties": {"name": {"type": "string"}, "role": {"type": "string"}, "prompt": {"type": "string"}}, "required": ["name", "role", "prompt"]}},
    {"name": "list_teammates", "description": "List all teammates.",
     "input_schema": {"type": "object", "properties": {}}},
    {"name": "send_message", "description": "Send a message to a teammate.",
     "input_schema": {"type": "object", "properties": {"to": {"type": "string"}, "content": {"type": "string"}, "msg_type": {"type": "string", "enum": list(VALID_MSG_TYPES)}}, "required": ["to", "content"]}},
    {"name": "read_inbox", "description": "Read and drain the lead's inbox.",
     "input_schema": {"type": "object", "properties": {}}},
    {"name": "broadcast", "description": "Send message to all teammates.",
     "input_schema": {"type": "object", "properties": {"content": {"type": "string"}}, "required": ["content"]}},
    {"name": "shutdown_request", "description": "Request a teammate to shut down.",
     "input_schema": {"type": "object", "properties": {"teammate": {"type": "string"}}, "required": ["teammate"]}},
    {"name": "plan_approval", "description": "Approve or reject a teammate's plan.",
     "input_schema": {"type": "object", "properties": {"request_id": {"type": "string"}, "approve": {"type": "boolean"}, "feedback": {"type": "string"}}, "required": ["request_id", "approve"]}},
    {"name": "idle", "description": "Enter idle state.",
     "input_schema": {"type": "object", "properties": {}}},
    {"name": "claim_task", "description": "Claim a task from the board.",
     "input_schema": {"type": "object", "properties": {"task_id": {"type": "integer"}}, "required": ["task_id"]}},
]


# === SECTION: agent_loop ===
def agent_loop(messages: list):
    rounds_without_todo = 0
    while True:
        # s06: compression pipeline
        microcompact(messages)
        if estimate_tokens(messages) > TOKEN_THRESHOLD:
            print("[auto-compact triggered]")
            messages[:] = auto_compact(messages)
        # s08: drain background notifications
        notifs = BG.drain()
        if notifs:
            txt = "\n".join(f"[bg:{n['task_id']}] {n['status']}: {n['result']}" for n in notifs)
            messages.append({"role": "user", "content": f"<background-results>\n{txt}\n</background-results>"})
            messages.append({"role": "assistant", "content": "Noted background results."})
        # s10: check lead inbox
        inbox = BUS.read_inbox("lead")
        if inbox:
            messages.append({"role": "user", "content": f"<inbox>{json.dumps(inbox, indent=2)}</inbox>"})
            messages.append({"role": "assistant", "content": "Noted inbox messages."})
        # LLM call
        response = client.messages.create(
            model=MODEL, system=SYSTEM, messages=messages,
            tools=TOOLS, max_tokens=8000,
        )
        messages.append({"role": "assistant", "content": response.content})
        if response.stop_reason != "tool_use":
            return
        # Tool execution
        results = []
        used_todo = False
        manual_compress = False
        for block in response.content:
            if block.type == "tool_use":
                if block.name == "compress":
                    manual_compress = True
                handler = TOOL_HANDLERS.get(block.name)
                try:
                    output = handler(**block.input) if handler else f"Unknown tool: {block.name}"
                except Exception as e:
                    output = f"Error: {e}"
                print(f"> {block.name}: {str(output)[:200]}")
                results.append({"type": "tool_result", "tool_use_id": block.id, "content": str(output)})
                if block.name == "TodoWrite":
                    used_todo = True
        # s03: nag reminder (only when todo workflow is active)
        rounds_without_todo = 0 if used_todo else rounds_without_todo + 1
        if TODO.has_open_items() and rounds_without_todo >= 3:
            results.insert(0, {"type": "text", "text": "<reminder>Update your todos.</reminder>"})
        messages.append({"role": "user", "content": results})
        # s06: manual compress
        if manual_compress:
            print("[manual compact]")
            messages[:] = auto_compact(messages)


# === SECTION: repl ===
if __name__ == "__main__":
    history = []
    while True:
        try:
            query = input("\033[36ms_full >> \033[0m")
        except (EOFError, KeyboardInterrupt):
            break
        if query.strip().lower() in ("q", "exit", ""):
            break
        if query.strip() == "/compact":
            if history:
                print("[manual compact via /compact]")
                history[:] = auto_compact(history)
            continue
        if query.strip() == "/tasks":
            print(TASK_MGR.list_all())
            continue
        if query.strip() == "/team":
            print(TEAM.list_all())
            continue
        if query.strip() == "/inbox":
            print(json.dumps(BUS.read_inbox("lead"), indent=2))
            continue
        history.append({"role": "user", "content": query})
        agent_loop(history)
        print()