diff --git a/src/scheduler/scheduler.py b/src/scheduler/scheduler.py
new file mode 100644
index 00000000..6c9cab97
--- /dev/null
+++ b/src/scheduler/scheduler.py
@@ -0,0 +1,117 @@
+"""定时任务调度器"""
+import logging
+from apscheduler.schedulers.asyncio import AsyncIOScheduler
+from datetime import datetime
+
+from src.config import settings
+from src.scheduler.jobs import (
+    job_step1_search,
+    job_step2_page,
+    job_step3_next,
+    job_step4_detail,
+    job_step5_crawl,
+    job_periodic_crawl,
+    job_check_validity,
+    job_generate_company,
+)
+
+logger = logging.getLogger(__name__)
+
+# 创建调度器
+scheduler = AsyncIOScheduler(
+    job_defaults={
+        'coalesce': True,  # 合并错过的任务
+        'max_instances': 3,  # 同一任务最多3个实例并发
+    }
+)
+
+
+def start_scheduler():
+    """启动调度器并注册所有任务"""
+    
+    # Step 1: 搜索招聘页面
+
+    scheduler.add_job(
+        job_step1_search,
+        'interval',
+        seconds=settings.job_step1_search_interval,
+        id='job_step1_search',
+        max_instances=2,
+        name='搜索招聘页面',
+        next_run_time=datetime.now()  # 立即执行第一次
+    )
+
+    # Step 2: 岗位列表分析
+    scheduler.add_job(
+        job_step2_page,
+        'interval',
+        seconds=settings.job_step2_page_interval,
+        id='job_step2_page',
+        name='岗位列表分析'
+    )
+
+    # Step 3: 分页分析
+    scheduler.add_job(
+        job_step3_next,
+        'interval',
+        seconds=settings.job_step3_next_interval,
+        id='job_step3_next',
+        name='分页分析'
+    )
+
+    #Step 4: 详情页分析
+    scheduler.add_job(
+        job_step4_detail,
+        'interval',
+        seconds=settings.job_step4_detail_interval,
+        id='job_step4_detail',
+        name='详情页分析'
+    )
+
+    # Step 5: 数据爬取
+    scheduler.add_job(
+        job_step5_crawl,
+        'interval',
+        seconds=settings.job_step5_crawl_interval,
+        id='job_step5_crawl',
+        next_run_time=datetime.now(),
+        name='数据爬取'
+    )
+
+    # # 周期爬取
+    # scheduler.add_job(
+    #     job_periodic_crawl,
+    #     'interval',
+    #     seconds=settings.job_periodic_crawl_interval,
+    #     id='job_periodic_crawl',
+    #     name='周期爬取'
+    # )
+    #
+    # # 有效性检查
+    # scheduler.add_job(
+    #     job_check_validity,
+    #     'interval',
+    #     seconds=settings.job_check_validity_interval,
+    #     id='job_check_validity',
+    #     name='有效性检查'
+    # )
+
+    # AI生成公司名
+    scheduler.add_job(
+        job_generate_company,
+        'interval',
+        seconds=settings.job_generate_company_interval,
+        id='job_generate_company',
+        max_instances=1,  # 单实例
+        next_run_time=datetime.now(),
+        name='AI生成公司名'
+    )
+
+    scheduler.start()
+    logger.info("定时任务调度器已启动")
+
+
+def shutdown_scheduler():
+    """关闭调度器"""
+    scheduler.shutdown()
+    logger.info("定时任务调度器已关闭")
diff --git a/src/search_company_graph/__init__.py b/src/search_company_graph/__init__.py
new file mode 100644
index 00000000..2e39d57d
--- /dev/null
+++ b/src/search_company_graph/__init__.py
@@ -0,0 +1,4 @@
+"""搜索公司招聘页面模块"""
+from .main import search_company_recruitment
+
+__all__ = ["search_company_recruitment"]
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diff --git a/src/search_company_graph/__pycache__/state.cpython-312.pyc b/src/search_company_graph/__pycache__/state.cpython-312.pyc
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diff --git a/src/search_company_graph/graph.py b/src/search_company_graph/graph.py
new file mode 100644
index 00000000..720ced6b
--- /dev/null
+++ b/src/search_company_graph/graph.py
@@ -0,0 +1,105 @@
+"""LangGraph 流程定义"""
+from langgraph.graph import StateGraph, END
+from .state import SearchState
+from .nodes import search_sogou, extract_links, visit_and_verify, navigate_to_recruitment
+
+
+def route_entry(state: SearchState) -> str:
+    """入口路由：有已知候选链接则跳过搜索"""
+    if state.get("candidate_urls"):
+        return "has_url"
+    return "need_search"
+
+
+def check_links(state: SearchState) -> str:
+    """检查是否有候选链接"""
+    urls = state.get("candidate_urls", [])
+    if not urls:
+        return "no_links"
+    return "has_links"
+
+
+def check_verify_result(state: SearchState) -> str:
+    """检查验证结果"""
+    # 已找到招聘列表页
+    if state.get("result_url"):
+        return "found"
+    
+    # 有错误（候选用完）
+    if state.get("error"):
+        return "failed"
+    
+    # 未找到，需要跳转
+    return "need_navigate"
+
+
+def check_navigate_result(state: SearchState) -> str:
+    """检查导航后的状态"""
+    current_url_index = state.get("current_url_index", 0)
+    candidate_urls = state.get("candidate_urls", [])
+    
+    # 候选用完
+    if current_url_index >= len(candidate_urls):
+        return "no_more_candidates"
+    
+    # 回 Node 3 验证
+    return "verify"
+
+
+def create_graph() -> StateGraph:
+    """创建流程图"""
+    
+    graph = StateGraph(SearchState)
+    
+    # 添加节点
+    graph.add_node("route_entry", lambda state: state)  # 路由节点，不修改状态
+    graph.add_node("search_sogou", search_sogou)
+    graph.add_node("extract_links", extract_links)
+    graph.add_node("visit_and_verify", visit_and_verify)
+    graph.add_node("navigate_to_recruitment", navigate_to_recruitment)
+    
+    # 入口路由
+    graph.set_entry_point("route_entry")
+    
+    # 路由：有已知URL直接验证，否则走搜索
+    graph.add_conditional_edges(
+        "route_entry",
+        route_entry,
+        {
+            "has_url": "visit_and_verify",
+            "need_search": "search_sogou"
+        }
+    )
+    
+    # 流程
+    graph.add_edge("search_sogou", "extract_links")
+    
+    graph.add_conditional_edges(
+        "extract_links",
+        check_links,
+        {
+            "no_links": END,
+            "has_links": "visit_and_verify"
+        }
+    )
+    
+    graph.add_conditional_edges(
+        "visit_and_verify",
+        check_verify_result,
+        {
+            "found": END,
+            "failed": END,
+            "need_navigate": "navigate_to_recruitment"
+        }
+    )
+    
+    graph.add_conditional_edges(
+        "navigate_to_recruitment",
+        check_navigate_result,
+        {
+            "no_more_candidates": END,
+            "verify": "visit_and_verify"
+        }
+    )
+    
+    return graph.compile()
diff --git a/src/search_company_graph/main.py b/src/search_company_graph/main.py
new file mode 100644
index 00000000..037498fb
--- /dev/null
+++ b/src/search_company_graph/main.py
@@ -0,0 +1,88 @@
+"""入口"""
+import asyncio
+import sys
+from pathlib import Path
+
+# 支持直接运行
+if __name__ == "__main__":
+    sys.path.insert(0, str(Path(__file__).parent.parent.parent))
+
+from playwright.async_api import async_playwright
+from playwright_stealth import Stealth
+from src.search_company_graph.graph import create_graph
+
+
+async def search_company_recruitment(company_name: str, input_url: str = None, headless: bool = False) -> list[str]:
+    """
+    搜索公司招聘列表页面
+    
+    Args:
+        company_name: 公司名称
+        input_url: 已知招聘地址(可选)，有值时跳过搜索直接验证
+        headless: 是否无头模式
+        
+    Returns:
+        list[str]: 招聘列表页 URL 列表，失败返回空列表
+    """
+    async with async_playwright() as p:
+        browser = await p.chromium.launch(headless=headless, channel="chrome")
+        context = await browser.new_context()
+        
+        # 应用 stealth
+        stealth = Stealth()
+        await stealth.apply_stealth_async(context)
+        
+        page = await context.new_page()
+        
+        try:
+            graph = create_graph()
+            
+            initial_state = {
+                "company_name": company_name,
+                "page": page
+            }
+            
+            # 已知URL时，直接作为候选链接跳过搜索
+            if input_url:
+                initial_state["candidate_urls"] = [input_url]
+                initial_state["current_url_index"] = 0
+                initial_state["clicked_selectors"] = []
+                initial_state["navigate_retry_count"] = 0
+            
+            print(f"\n{'='*50}")
+            print(f"开始搜索: {company_name}")
+            print(f"{'='*50}\n")
+            
+            final_state = await graph.ainvoke(initial_state)
+            
+            print(f"\n{'='*50}")
+            print("搜索完成")
+            print(f"{'='*50}\n")
+            
+            # 返回结果
+            result_url = final_state.get("result_url")
+            if result_url:
+                return [result_url]
+            return []
+            
+        finally:
+            await browser.close()
+
+
+async def main():
+    """测试"""
+    company_name = "五粮液"
+
+    result = await search_company_recruitment(company_name)
+    
+    print("\n最终结果:")
+    if result:
+        print(f"✅ 成功找到招聘页面:")
+        for url in result:
+            print(f"   {url}")
+    else:
+        print("❌ 未找到招聘页面")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/src/search_company_graph/nodes.py b/src/search_company_graph/nodes.py
new file mode 100644
index 00000000..7eadf1b3
--- /dev/null
+++ b/src/search_company_graph/nodes.py
@@ -0,0 +1,457 @@
+"""节点实现"""
+import asyncio
+from pydantic import BaseModel, Field
+from langchain_core.messages import HumanMessage
+from src.bash_model import GeneralLlm
+from .state import SearchState
+from .prompts import EXTRACT_LINKS_PROMPT, VERIFY_RECRUITMENT_LIST_PROMPT, FIND_RECRUITMENT_ENTRY_PROMPT
+
+
+# 结构化输出模型
+class ExtractLinksResult(BaseModel):
+    """提取链接结果"""
+    urls: list[str] = Field(description="候选URL列表，最多3个")
+    reason: str = Field(description="选择理由")
+
+
+class VerifyResult(BaseModel):
+    """验证结果"""
+    is_recruitment_list: bool = Field(description="是否为招聘列表页")
+    reason: str = Field(description="判断依据")
+
+
+class FindEntryResult(BaseModel):
+    """找入口结果"""
+    selector: str | None = Field(description="CSS选择器，找不到则为None")
+    reason: str = Field(description="选择或找不到的原因")
+
+
+async def get_clean_html(page, max_retries: int = 3) -> str:
+    """获取清理后的页面 HTML（移除 style/script 等），带重试逻辑"""
+    for attempt in range(max_retries):
+        try:
+            # 等待页面加载稳定
+            try:
+                await page.wait_for_load_state("domcontentloaded", timeout=5000)
+            except Exception:
+                pass
+            
+            # 额外等待一下，确保页面不再跳转
+            await asyncio.sleep(1)
+            
+            html = await page.evaluate("""
+                () => {
+                    const clone = document.body.cloneNode(true);
+                    clone.querySelectorAll('style, script, noscript, svg, link').forEach(el => el.remove());
+                    return clone.innerHTML;
+                }
+            """)
+            return html
+        except Exception as e:
+            if attempt < max_retries - 1:
+                # 可能是页面正在跳转，等待后重试
+                await asyncio.sleep(2)
+            else:
+                # 最后一次尝试失败，返回空字符串
+                print(f"[get_clean_html] 获取页面内容失败: {e}")
+                return ""
+
+
+async def get_search_results(page) -> str:
+    """提取搜狗搜索结果（结构化文本），并解析搜狗跳转链接获取真实 URL"""
+    # 第一步：提取搜索结果基本信息
+    raw_results = await page.evaluate("""
+        () => {
+            // 获取自然搜索结果（排除广告和推荐框）
+            const results = document.querySelectorAll('.vrwrap:not(.middle-better-hintBox)');
+            if (!results.length) return [];
+            
+            return Array.from(results).map((el, i) => {
+                const title = el.querySelector('.vr-title a, h3 a')?.innerText?.trim() || '';
+                
+                // 优先从后续的 .r-sech 元素的 data-url 获取完整 URL
+                let url = '';
+                const nextEl = el.nextElementSibling;
+                if (nextEl && nextEl.classList.contains('r-sech')) {
+                    url = nextEl.getAttribute('data-url') || '';
+                }
+                
+                // 备选：从链接 href 获取
+                if (!url) {
+                    const linkEl = el.querySelector('.vr-title a, h3 a');
+                    url = linkEl?.href || '';
+                }
+                
+                const desc = el.querySelector('.fz-mid, .star-wiki')?.innerText?.trim() || '';
+                return { title, url, desc };
+            }).filter(item => item.url && (item.url.startsWith('http://') || item.url.startsWith('https://')));
+        }
+    """)
+    
+    if not raw_results:
+        # 回退到纯文本提取
+        return await page.evaluate("() => document.body.innerText.slice(0, 30000)")
+    
+    # 第二步：解析搜狗跳转链接获取真实 URL
+    resolved_results = []
+    for item in raw_results:
+        url = item.get('url', '')
+        
+        # 如果是搜狗跳转链接，尝试解析真实 URL
+        if 'sogou.com/link' in url:
+            try:
+                real_url = await resolve_sogou_redirect(page, url)
+                if real_url:
+                    url = real_url
+            except Exception:
+                pass  # 解析失败则保留原 URL
+        
+        resolved_results.append({
+            'title': item.get('title', ''),
+            'url': url,
+            'desc': item.get('desc', '')
+        })
+    
+    # 第三步：格式化输出
+    output_lines = []
+    for i, item in enumerate(resolved_results):
+        output_lines.append(f"{i+1}. {item['title']}\nURL: {item['url']}\n{item['desc']}")
+    
+    return "\n\n".join(output_lines)
+
+
+async def resolve_sogou_redirect(page, sogou_url: str) -> str:
+    """解析搜狗跳转链接，获取真实目标 URL"""
+    try:
+        # 使用 fetch 获取跳转页面内容
+        response_text = await page.evaluate("""
+            async (url) => {
+                try {
+                    const resp = await fetch(url, { redirect: 'manual' });
+                    const text = await resp.text();
+                    return text;
+                } catch (e) {
+                    return '';
+                }
+            }
+        """, sogou_url)
+        
+        if not response_text:
+            return ''
+        
+        # 从 meta refresh 标签提取真实 URL
+        # 匹配模式: <META http-equiv="refresh" content="0;URL='http://xxx.com/'">
+        import re
+        match = re.search(r"URL='([^']+)'", response_text, re.IGNORECASE)
+        if match:
+            return match.group(1)
+        
+        # 备选匹配模式: url=http://xxx.com
+        match = re.search(r'url=([^"\s>]+)', response_text, re.IGNORECASE)
+        if match:
+            return match.group(1)
+        
+        return ''
+    except Exception:
+        return ''
+
+
+async def search_sogou(state: SearchState) -> dict:
+    """Node 1: 搜狗搜索"""
+    page = state["page"]
+    company_name = state["company_name"]
+    
+    print(f"[Node 1] 搜狗搜索: {company_name} 校园招聘 官网")
+    
+    # 访问搜狗
+    await page.goto("https://www.sogou.com")
+    await asyncio.sleep(1)
+    
+    # 搜索
+    await page.fill('input[name="query"]', f"{company_name}  校园招聘 官网")
+    await page.press('input[name="query"]', "Enter")
+    try:
+        await page.wait_for_load_state("networkidle", timeout=10000)
+    except Exception:
+        pass  # 超时也继续
+    await asyncio.sleep(2)
+    
+    # 获取搜索结果（结构化文本）
+    search_result_text = await get_search_results(page)
+    
+    print(f"[Node 1] 获取搜索结果完成，长度: {len(search_result_text)}")
+
+    # 强制删除微公众号信息网页
+    search_result_text = search_result_text.replace("mp.weixin.qq.com", "")
+    
+    return {"search_result_html": search_result_text}
+
+
+async def extract_links(state: SearchState) -> dict:
+    """Node 2: 提取候选链接"""
+    search_text = state["search_result_html"]
+    company_name = state["company_name"]
+    
+    print("[Node 2] 分析搜索结果，提取候选链接...")
+    
+    # LLM 分析
+    prompt = EXTRACT_LINKS_PROMPT.format(company_name=company_name, html=search_text)
+    llm = GeneralLlm.with_structured_output(ExtractLinksResult)
+    
+    try:
+        result = await llm.ainvoke([HumanMessage(content=prompt)])
+    except Exception as e:
+        print(f"[Node 2] LLM 调用失败: {e}")
+        return {
+            "candidate_urls": [],
+            "current_url_index": 0,
+            "clicked_selectors": [],
+            "navigate_retry_count": 0
+        }
+    
+    # 规范化 URL（确保有协议前缀）
+    normalized_urls = []
+    for url in result.urls:
+        if url and not url.startswith(('http://', 'https://')):
+            url = 'https://' + url
+        if url:
+            normalized_urls.append(url)
+    
+    print(f"[Node 2] 提取到 {len(normalized_urls)} 个候选链接:")
+    for i, url in enumerate(normalized_urls):
+        print(f"  {i+1}. {url}")
+    
+    return {
+        "candidate_urls": normalized_urls,
+        "current_url_index": 0,
+        "clicked_selectors": [],
+        "navigate_retry_count": 0
+    }
+
+
+async def visit_and_verify(state: SearchState) -> dict:
+    """Node 3: 访问并验证是否为招聘列表页"""
+    context = state["page"].context
+    candidate_urls = state.get("candidate_urls", [])
+    current_url_index = state.get("current_url_index", 0)
+    
+    # 确保有有效页面
+    if not context.pages:
+        page = await context.new_page()
+    else:
+        # 只保留最新的页面
+        page = context.pages[-1]
+        for p in context.pages[:-1]:
+            try:
+                await p.close()
+            except Exception:
+                pass
+    
+    # 检查是否还有候选链接
+    if current_url_index >= len(candidate_urls):
+        print("[Node 3] 候选链接已用完")
+        return {"error": "所有候选链接均未找到招聘列表页"}
+    
+    current_url = candidate_urls[current_url_index]
+    clicked_selectors = state.get("clicked_selectors", [])
+    
+    # 判断是否从 Node 4 跳转回来（已经点击过入口）
+    if clicked_selectors:
+        # 从 Node 4 返回，直接使用当前页面
+        print(f"[Node 3] 验证跳转后的页面: {page.url}")
+        page_html = await get_clean_html(page)
+    else:
+        # 首次访问该候选链接
+        print(f"[Node 3] 访问候选链接 {current_url_index + 1}/{len(candidate_urls)}: {current_url}")
+        
+        # 重试机制
+        max_retries = 3
+        for attempt in range(max_retries):
+            try:
+                await page.goto(current_url, wait_until="domcontentloaded", timeout=20000)
+                # 等待页面稳定（处理可能的跳转）
+                await asyncio.sleep(2)
+                try:
+                    await page.wait_for_load_state("networkidle", timeout=5000)
+                except Exception:
+                    pass
+                await asyncio.sleep(1)
+                break
+            except Exception as e:
+                print(f"[Node 3] 访问失败 ({attempt + 1}/{max_retries}): {e}")
+                if attempt == max_retries - 1:
+                    return {
+                        "current_url": current_url,
+                        "current_url_index": current_url_index + 1,
+                        "clicked_selectors": [],
+                        "navigate_retry_count": 0
+                    }
+                await asyncio.sleep(2)
+        
+        # 获取页面内容
+        page_html = await get_clean_html(page)
+        
+        # 如果获取失败，尝试下一个候选
+        if not page_html:
+            print("[Node 3] 获取页面内容失败，尝试下一个候选")
+            return {
+                "current_url": current_url,
+                "current_url_index": current_url_index + 1,
+                "clicked_selectors": [],
+                "navigate_retry_count": 0
+            }
+    
+    # 截断
+    display_html = page_html
+    # if len(display_html) > 50000:
+    #     display_html = display_html[:50000] + "\n... (已截断)"
+    
+    # LLM 判断
+    prompt = VERIFY_RECRUITMENT_LIST_PROMPT.format(html=display_html)
+    llm = GeneralLlm.with_structured_output(VerifyResult)
+    
+    try:
+        result = await llm.ainvoke([HumanMessage(content=prompt)])
+    except Exception as e:
+        print(f"[Node 3] LLM 调用失败: {e}")
+        # LLM 失败，尝试下一个候选
+        return {
+            "current_url": current_url,
+            "current_url_index": current_url_index + 1,
+            "clicked_selectors": [],
+            "navigate_retry_count": 0
+        }
+    
+    print(f"[Node 3] 是否为招聘列表页: {result.is_recruitment_list}")
+    print(f"[Node 3] 原因: {result.reason}")
+    
+    if result.is_recruitment_list:
+        return {
+            "current_url": current_url,
+            "page_html": page_html,
+            "result_url": page.url  # 使用实际 URL（可能有跳转）
+        }
+    
+    return {
+        "current_url": current_url,
+        "page_html": page_html
+    }
+
+
+async def navigate_to_recruitment(state: SearchState) -> dict:
+    """Node 4: 找入口并跳转"""
+    context = state["page"].context
+    
+    # 确保有有效页面
+    if not context.pages:
+        # 没有页面了，换下一个候选
+        current_url_index = state.get("current_url_index", 0)
+        return {
+            "current_url_index": current_url_index + 1,
+            "clicked_selectors": [],
+            "navigate_retry_count": 0
+        }
+    page = context.pages[-1]
+    
+    page_html = state.get("page_html", "")
+    clicked_selectors = state.get("clicked_selectors", [])
+    navigate_retry_count = state.get("navigate_retry_count", 0)
+    current_url_index = state.get("current_url_index", 0)
+    
+    print(f"[Node 4] 尝试找跳转入口 (第 {navigate_retry_count + 1}/10 次)")
+    
+    # 检查重试次数
+    if navigate_retry_count >= 5:
+        print("[Node 4] 已尝试 5 次，换下一个候选链接")
+        return {
+            "current_url_index": current_url_index + 1,
+            "clicked_selectors": [],
+            "navigate_retry_count": 0
+        }
+    
+    # 检查 page_html 是否有效
+    if not page_html or len(page_html) < 100:
+        print("[Node 4] page_html 无效，重新获取")
+        page_html = await get_clean_html(page)
+        if not page_html or len(page_html) < 100:
+            print("[Node 4] 页面内容仍无效，换下一个候选")
+            return {
+                "current_url_index": current_url_index + 1,
+                "clicked_selectors": [],
+                "navigate_retry_count": 0
+            }
+    
+    # 截断 HTML
+    display_html = page_html
+    # if len(display_html) > 50000:
+    #     display_html = display_html[:50000] + "\n... (已截断)"
+    
+    # LLM 分析
+    clicked_str = "\n".join(clicked_selectors) if clicked_selectors else "无"
+    prompt = FIND_RECRUITMENT_ENTRY_PROMPT.format(
+        html=display_html,
+        clicked_selectors=clicked_str
+    )
+    llm = GeneralLlm.with_structured_output(FindEntryResult)
+    
+    try:
+        result = await llm.ainvoke([HumanMessage(content=prompt)])
+    except Exception as e:
+        print(f"[Node 4] LLM 调用失败: {e}")
+        return {
+            "page_html": page_html,
+            "clicked_selectors": clicked_selectors,
+            "navigate_retry_count": navigate_retry_count + 1
+        }
+    
+    if not result.selector:
+        print(f"[Node 4] 未找到入口: {result.reason}")
+        # 找不到也计入重试，继续循环
+        return {
+            "page_html": page_html,
+            "clicked_selectors": clicked_selectors,
+            "navigate_retry_count": navigate_retry_count + 1
+        }
+    
+    print(f"[Node 4] 找到入口: {result.selector}")
+    print(f"[Node 4] 原因: {result.reason}")
+    
+    # 记录点击前的状态
+    tabs_before = len(context.pages)
+    
+    try:
+        element = page.locator(result.selector).first
+        await element.scroll_into_view_if_needed()
+        await asyncio.sleep(0.2)
+        await element.hover()
+        await asyncio.sleep(0.3)
+        await element.click()
+        await asyncio.sleep(3)
+    except Exception as e:
+        print(f"[Node 4] 点击失败: {e}")
+        return {
+            "page_html": page_html,
+            "clicked_selectors": clicked_selectors + [result.selector],
+            "navigate_retry_count": navigate_retry_count + 1
+        }
+    
+    # 检查是否打开新标签页
+    tabs_after = len(context.pages)
+    if tabs_after > tabs_before:
+        page = context.pages[-1]
+        print(f"[Node 4] 打开新标签页: {page.url}")
+    
+    # 等待页面加载
+    try:
+        await page.wait_for_load_state("networkidle", timeout=10000)
+    except Exception:
+        pass
+    
+    new_html = await get_clean_html(page)
+    print(f"[Node 4] 点击后页面: {page.url}")
+    
+    return {
+        "page_html": new_html,
+        "clicked_selectors": clicked_selectors + [result.selector],
+        "navigate_retry_count": navigate_retry_count + 1
+    }
diff --git a/src/search_company_graph/prompts.py b/src/search_company_graph/prompts.py
new file mode 100644
index 00000000..179a68b4
--- /dev/null
+++ b/src/search_company_graph/prompts.py
@@ -0,0 +1,119 @@
+"""LLM 提示词"""
+
+# Node 2: 从搜索结果提取链接
+EXTRACT_LINKS_PROMPT = """分析以下搜狗搜索结果，找出最可能是 {company_name} 校园招聘 官方页面的链接。
+
+## 搜索结果
+{html}
+
+## 任务
+从上面的搜索结果中提取最可能的官网页面 URL（最多3个），按可能性排序，并去重。
+
+## 优先级
+1. 公司官网的招聘频道（如 careers.xxx.com, jobs.xxx.com, xxx.com/careers, talent.xxx.com）
+2. 公司官网首页
+
+## 排除
+- 新闻、资讯页面
+- 招聘相关但非该公司的页面
+- 第三方招聘地址
+- 和{company_name}公司无关地址
+
+## 输出
+仅输出 JSON:
+{{
+  "urls": ["https://xxx.com/careers"],
+  "reason": "选择理由"  #字数限制15字
+}}
+
+找不到则:
+{{
+  "urls": [],
+  "reason": "原因" #字数限制15字
+}}
+"""
+
+# Node 3: 判断是否为岗位列表页
+VERIFY_RECRUITMENT_LIST_PROMPT = """判断以下页面是否为岗位列表页。
+
+## 页面 HTML
+{html}
+
+## 判断标准
+是岗位列表页（举例）：
+- 展示多个岗位/职位的页面
+- 平铺展示多个岗位的页面（无分页）
+- 有列表结构但显示「暂无岗位」的空列表页
+
+## 严格标准
+“是岗位列表页”必须满足以下条件之一：
+
+### 情况1：有岗位数据
+- 页面包含 >= 2 个岗位信息
+- 每个岗位至少有：岗位名称、工作地点/薪资/发布时间之一
+- 岗位以列表/卡片/表格形式展示
+
+### 情况2：空列表页（无岗位数据）
+必须同时满足以下所有条件：
+1. 存在明确的空状态提示，如：
+   - "暂无岗位"、"无符合条件的职位"、"No results"、"暂无数据"
+   - 空列表图标 + 提示文字
+2. 存在岗位筛选/搜索功能，如：
+   - 岗位类型下拉框、地点筛选、关键词搜索框
+3. 页面结构简洁，主体区域明显是用于展示列表
+
+### 不是岗位列表页的情况
+- 只有招聘宣传语（如"加入我们"、"企业文化"），无岗位展示区域
+- 只有招聘流程介绍，无具体岗位
+- 只有公司介绍/团队介绍
+- 只有单个岗位的详情页
+- 纯导航页/入口页（需要点击才能看到岗位）
+
+不是岗位列表页（举例）：
+- 单个岗位详情页
+- 公司介绍页
+- 招聘宣传页（无岗位列表区域）
+
+根据以上示例，判断当前页面更接近哪一类。
+
+## 输出
+仅输出 JSON:
+{{
+  "is_recruitment_list": true或false,
+  "reason": "判断依据" #字数限制20字
+}}
+"""
+
+# Node 4: 找跳转入口
+FIND_RECRUITMENT_ENTRY_PROMPT = """分析以下页面，找出最可能跳转到校园招聘岗位列表的元素。
+
+## 页面 HTML
+{html}
+
+## 已尝试过的选择器（避免使用）
+{clicked_selectors}
+
+## 任务
+找到一个最可能通向招聘岗位列表的可点击元素。
+
+## 可能的线索
+- 文字：招聘、加入我们、社会招聘、校园招聘、查看职位、岗位列表、人才、career、jobs、join us ...
+- 搜索按钮、搜索图标（点击后可能展示岗位列表）
+- 导航菜单中的相关项
+- 页面主体区域的按钮或链接
+- 即使没有明确招聘文字，也可能是通向招聘的入口
+- 根据您的理解选择可能连接到岗位列表的线索
+
+## 输出
+仅输出 JSON:
+{{
+  "selector": "CSS选择器",
+  "reason": "选择原因" #字数限制30字
+}}
+
+找不到则:
+{{
+  "selector": null,
+  "reason": "原因"  #字数限制15字
+}}
+"""
diff --git a/src/search_company_graph/state.py b/src/search_company_graph/state.py
new file mode 100644
index 00000000..dad31eae
--- /dev/null
+++ b/src/search_company_graph/state.py
@@ -0,0 +1,31 @@
+"""状态定义"""
+from typing import TypedDict
+from playwright.async_api import Page
+
+
+class SearchState(TypedDict, total=False):
+    """搜索公司招聘页面的状态"""
+    
+    # 输入
+    company_name: str
+    page: Page
+    
+    # Node 1: search_sogou
+    search_result_html: str
+    
+    # Node 2: extract_links
+    candidate_urls: list[str]      # 候选链接列表（最多3个）
+    current_url_index: int         # 当前尝试的索引
+    
+    # Node 3: visit_and_verify
+    current_url: str               # 当前访问的 URL
+    page_html: str                 # 当前页面 HTML
+    
+    # Node 4: navigate_to_recruitment
+    clicked_selectors: list[str]   # 已点击过的选择器
+    navigate_retry_count: int      # 页内跳转重试次数（上限10次）
+    page_changed: bool             # 点击后页面是否变化
+    
+    # 结果
+    result_url: str                # 最终找到的招聘列表页 URL
+    error: str                     # 错误信息
diff --git a/test_crawler.py b/test_crawler.py
new file mode 100644
index 00000000..0a6887ec
--- /dev/null
+++ b/test_crawler.py
@@ -0,0 +1,62 @@
+"""Crawler 测试脚本"""
+import asyncio
+from src.crawler import crawl, CrawlerConfig
+
+
+# 中兴招聘测试配置
+# test_config: CrawlerConfig = {
+#     "url": "https://app.mokahr.com/social-recruitment/zte/47588#/jobs",
+#     "job_item_selector": ".jobs-list-WmE84RgZxp .container-aOp138AX_X.normal-TBuWTpDMcE.list-oR2doUijv4",
+#     "item_change_type": "redirect",
+#     "next_page_selector": ".sd-Pagination-pagination-2kuN2 .sd-Pagination-forward-3z80f",
+#     "page_change_type": "url_change",
+#     "field_selectors": {
+#         "job_title": {"selector": [".title-ROUQFdjmhP"]},
+#         "description": {"selector": [".job-description-VvfEUGocNE"]},
+#         "location": {"selector": [".info-UcB_mxJq8y span:first-child"]},
+#         "company": {"selector": [".basic-info-dB86EjV5uU span:nth-child(2)"]},
+#     },
+#     "detail_area_selector": None,
+# }
+
+# 美宜佳招聘测试配置
+# test_config: CrawlerConfig = {
+#     "url": "https://meiyijia.jobs.feishu.cn/social/position/list",
+#     "job_item_selector": ".listItems__fca8c0 a",
+#     "item_change_type": "new_tab",
+#     "next_page_selector": ".pager__fca8c0 .atsx-pagination-next:not(.atsx-pagination-disabled)",
+#     "page_change_type": "url_change",
+#     "field_selectors": {
+#         "job_title": {"selector": [".positionItem-title-text"]},
+#         "description": {"selector": [".positionItem-jobDesc"]},
+#         "location": {"selector": [".positionItem-subTitle span"]},
+#     },
+#     "detail_area_selector": None,
+# }
+
+# 三星招聘测试配置
+test_config: CrawlerConfig = {
+    "url": "https://dearsamsung.zhiye.com/#/samsung/pc/szzw",
+    "job_item_selector": ".BHGkB li",
+    "item_change_type": "in_page",
+    "next_page_selector": "._8x6MD .ant-pagination-next:not([aria-disabled='true']) .ant-pagination-item-link",
+    "page_change_type": "content_change",
+    "field_selectors": {
+        "job_title": {"selector": ["h2"]},
+        "description": {"selector": ['.aCl-8 p', '.aCl-8 pre']},
+    },
+    "detail_area_selector": ".FLf6j",
+}
+
+
+async def main():
+    results = await crawl(test_config, headless=False)
+    print(f"\n爬取完成，共 {len(results)} 条数据")
+    for i, item in enumerate(results):
+        print(f"\n--- 岗位 {i+1} ---")
+        for k, v in item.items():
+            print(f"{k}: {v}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())