feat(memory): 新增项目记忆检索工具 search_project_memory

- 后端：关键词全文检索 .astrion/memory/*.md（名称+10/描述+5/正文加权），
  返回 top-N 与带行号片段；注册为主 agent 只读工具，子智能体工具集同步；
  memory_system 模板与多智能体 prompt 增加检索指引（第二触点）
- 工具 description 含硬性触发条件、query 撰写指引、负例与防重试契约
- 前端：新增 notebook-search 组合图标（notebook 轮廓开口 + 右下角放大镜）；
  工具详情渲染命中记忆的名称/描述/行号片段；活动汇总归入 memory_read
- 重构：ToolAction.vue 删除约 1600 行重复渲染函数，统一委托
  toolRenderers.ts（与 StackedBlocks/MinimalBlocks 同一实现）

core/main_terminal_parts/tools_definition/context_tools.py

@@ -109,7 +109,7 @@ class ToolsDefinitionContextToolsMixin:
                         "type": "function",
                         "function": {
                             "name": "recall_project_memory",
-                            "description": "读取指定的项目记忆文件，返回完整内容（含 frontmatter）。项目记忆存储在 .astrion/memory/ 目录下。",
+                            "description": "读取指定的项目记忆文件，返回完整内容（含 frontmatter）。项目记忆存储在 .astrion/memory/ 目录下。通常在 search_project_memory 检索定位后使用；若不确定记忆名称，先检索再读取。",
                             "parameters": {
                                 "type": "object",
                                 "properties": self._inject_intent({
@@ -125,6 +125,31 @@ class ToolsDefinitionContextToolsMixin:
 
                                     {
                         "type": "function",
+                        "function": {
+                            "name": "search_project_memory",
+                            "description": "在项目记忆文件（.astrion/memory/*.md）的正文和描述中全文检索，返回匹配的记忆文件与片段。【硬性要求】开始处理与本项目相关的任务前（修改代码、调试报错、配置部署，或任务可能涉及项目约定/历史决策/已知问题时），必须先调用本工具检索；根据任务内容、用户要求和项目记忆索引中的描述，提取2~5个清晰精确的关键词（优先使用项目术语、模块名、文件名、报错文本，中英文均可）。纯闲聊、与项目无关的通用问题不要调用。未命中时会明确返回无结果，此时不要更换同义词重复尝试；命中后如需完整内容，用 recall_project_memory 读取。",
+                            "parameters": {
+                                "type": "object",
+                                "properties": self._inject_intent({
+                                    "keywords": {
+                                        "type": "array",
+                                        "description": "搜索关键词列表，建议2~5个；任一关键词命中即算匹配，命中数越多排名越靠前",
+                                        "items": {"type": "string"},
+                                        "minItems": 1,
+                                        "maxItems": 5
+                                    },
+                                    "max_results": {
+                                        "type": "integer",
+                                        "description": "最多返回多少条匹配记忆，默认5，最大10"
+                                    }
+                                }),
+                                "required": ["keywords"]
+                            }
+                        }
+                    },
+
+                                    {
+                        "type": "function",
                         "function": {
                             "name": "update_project_memory",
                             "description": "创建或覆盖项目记忆文件。当你发现有关当前项目的重要约定/决策/坑、用户表现出对项目的偏好，或用户主动要求「在当前项目里，下次要xxx/记住xxx」时，应积极主动地调用本工具。记忆名称用英文下划线，描述格式为'当xxxx时，应该索引本记忆'。不记录可从代码直接推断的或一次性信息。",

core/main_terminal_parts/tools_execution.py

@@ -192,6 +192,7 @@ class MainTerminalToolsExecutionMixin:
         "ocr_image",
         "update_memory",
         "recall_project_memory",
+        "search_project_memory",
         "update_project_memory",
         "conversation_search",
         "conversation_review",
@@ -1746,6 +1747,25 @@ class MainTerminalToolsExecutionMixin:
                         else:
                             result = self._handle_recall_project_memory(name)
 
+                    elif tool_name == "search_project_memory":
+                        raw_keywords = arguments.get("keywords")
+                        if isinstance(raw_keywords, list):
+                            keywords = [
+                                str(item).strip()
+                                for item in raw_keywords
+                                if str(item or "").strip()
+                            ][:5]
+                        else:
+                            keywords = []
+                        if not keywords:
+                            result = {"success": False, "error": "search_project_memory 需要 keywords 参数（至少 1 个关键词）"}
+                        else:
+                            try:
+                                max_results = int(arguments.get("max_results") or 5)
+                            except Exception:
+                                max_results = 5
+                            result = self._handle_search_project_memory(keywords, max_results)
+
                     elif tool_name == "update_project_memory":
                         name = str(arguments.get("name", "")).strip()
                         description = str(arguments.get("description", "")).strip()

core/main_terminal_parts/tools_read.py

@@ -174,6 +174,139 @@ class MainTerminalToolsReadMixin:
                     result["memory_name"] = safe_name
                 return result
 
+    def _handle_search_project_memory(self, keywords: List[str], max_results: int = 5) -> Dict:
+                """处理 search_project_memory：在 .astrion/memory/*.md 中做关键词全文检索。
+
+                评分：名称命中 +10，描述命中 +5，正文每行命中 +1（单关键词最多计 5 行）。
+                返回 top-N 结果，附匹配行片段（行号基于完整文件，可直接配合 read_file extract 使用）。
+                """
+                clean_keywords: List[str] = []
+                for kw in keywords or []:
+                    kw_text = str(kw or "").strip()
+                    if kw_text and kw_text not in clean_keywords:
+                        clean_keywords.append(kw_text)
+                clean_keywords = clean_keywords[:5]
+                if not clean_keywords:
+                    return {"success": False, "error": "search_project_memory 需要至少 1 个关键词"}
+
+                max_results = self._clamp_int(max_results, 5, 1, 10)
+                memory_dir = Path(self.project_path) / WORKSPACE_MEMORY_DIRNAME
+                if not memory_dir.exists() or not memory_dir.is_dir():
+                    empty_text = "项目记忆目录不存在，暂无项目记忆可检索。"
+                    return {
+                        "success": True,
+                        "count": 0,
+                        "keywords": clean_keywords,
+                        "results": [],
+                        "content": empty_text,
+                        "summary": empty_text,
+                    }
+
+                lowered = [(kw, kw.lower()) for kw in clean_keywords]
+                scored: List[Dict[str, Any]] = []
+                for md_file in sorted(memory_dir.glob("*.md")):
+                    try:
+                        text = md_file.read_text(encoding="utf-8")
+                    except Exception:
+                        continue
+
+                    lines = text.split("\n")
+                    name = md_file.stem
+                    description = ""
+                    body_start_idx = 0  # 0-based，正文起始行（跳过 frontmatter）
+                    if lines and lines[0].strip() == "---":
+                        for i in range(1, len(lines)):
+                            if lines[i].strip() == "---":
+                                for fm_line in lines[1:i]:
+                                    fm_stripped = fm_line.strip()
+                                    if fm_stripped.startswith("name:"):
+                                        name = fm_stripped.split(":", 1)[1].strip() or name
+                                    elif fm_stripped.startswith("description:"):
+                                        description = fm_stripped.split(":", 1)[1].strip()
+                                body_start_idx = i + 1
+                                break
+
+                    name_lower = name.lower()
+                    desc_lower = description.lower()
+                    body_lines = lines[body_start_idx:]
+
+                    score = 0
+                    matched_keywords: List[str] = []
+                    for kw, kw_lower in lowered:
+                        kw_score = 0
+                        if kw_lower in name_lower:
+                            kw_score += 10
+                        if kw_lower in desc_lower:
+                            kw_score += 5
+                        body_hits = sum(1 for line in body_lines if kw_lower in line.lower())
+                        kw_score += min(body_hits, 5)
+                        if kw_score > 0:
+                            score += kw_score
+                            matched_keywords.append(kw)
+
+                    if score <= 0:
+                        continue
+
+                    snippets: List[Dict[str, Any]] = []
+                    for idx in range(body_start_idx, len(lines)):
+                        line_stripped = lines[idx].strip()
+                        if not line_stripped:
+                            continue
+                        line_lower = line_stripped.lower()
+                        if any(kw_lower in line_lower for _, kw_lower in lowered):
+                            snippet_text = line_stripped if len(line_stripped) <= 120 else line_stripped[:117] + "..."
+                            snippets.append({"line": idx + 1, "text": snippet_text})
+                        if len(snippets) >= 3:
+                            break
+
+                    scored.append({
+                        "file": md_file.name,
+                        "name": name,
+                        "description": description,
+                        "score": score,
+                        "matched_keywords": matched_keywords,
+                        "snippets": snippets,
+                    })
+
+                scored.sort(key=lambda item: (-item["score"], -len(item["matched_keywords"]), item["name"]))
+                top = scored[:max_results]
+
+                if not top:
+                    empty_text = (
+                        f"未找到匹配的项目记忆（关键词：{'、'.join(clean_keywords)}）。"
+                        "不要更换关键词重复检索；继续当前任务即可。"
+                    )
+                    return {
+                        "success": True,
+                        "count": 0,
+                        "keywords": clean_keywords,
+                        "results": [],
+                        "content": empty_text,
+                        "summary": "未找到匹配的项目记忆",
+                    }
+
+                content_lines = [f"找到 {len(top)} 个匹配的项目记忆（关键词：{'、'.join(clean_keywords)}）：", ""]
+                for rank, item in enumerate(top, start=1):
+                    content_lines.append(f"[{rank}] {item['name']}（.astrion/memory/{item['file']}）")
+                    if item["description"]:
+                        content_lines.append(f"    描述：{item['description']}")
+                    if item["snippets"]:
+                        content_lines.append("    匹配片段：")
+                        for snippet in item["snippets"]:
+                            content_lines.append(f"      L{snippet['line']}: {snippet['text']}")
+                    content_lines.append("")
+                content_lines.append("如需完整内容，使用 recall_project_memory 读取对应记忆。")
+                content_text = "\n".join(content_lines).strip()
+
+                return {
+                    "success": True,
+                    "count": len(top),
+                    "keywords": clean_keywords,
+                    "results": top,
+                    "content": content_text,
+                    "summary": f"找到 {len(top)} 个匹配的项目记忆",
+                }
+
     @staticmethod
     def _clamp_int(value, default, min_value=None, max_value=None):
                 """将输入转换为整数并限制范围。"""

modules/multi_agent/sub_agent_context.py

@@ -207,7 +207,7 @@ def _build_project_memory_section(workspace_path: str) -> str:
             f"## 项目记忆\n\n"
             f"项目记忆以文件形式存放在 `.astrion/memory/` 下。\n"
             f"开始涉及项目约定、历史决策或已知问题的任务前，先检查项目记忆索引，"
-            f"如有相关记忆则用 recall_project_memory 读取。\n\n"
+            f"不确定时先用 search_project_memory 检索正文，定位后用 recall_project_memory 读取。\n\n"
             f"### 项目记忆索引\n\n"
             + "\n".join(entries)
             + "\n"

modules/sub_agent/toolkit.py

@@ -177,7 +177,7 @@ SUB_AGENT_TOOLS: List[Dict[str, Any]] = [
         "type": "function",
         "function": {
             "name": "recall_project_memory",
-            "description": "读取指定的项目记忆文件，返回完整内容（含 frontmatter）。项目记忆存储在 .astrion/memory/ 目录下。",
+            "description": "读取指定的项目记忆文件，返回完整内容（含 frontmatter）。项目记忆存储在 .astrion/memory/ 目录下。通常在 search_project_memory 检索定位后使用；若不确定记忆名称，先检索再读取。",
             "parameters": {
                 "type": "object",
                 "properties": {
@@ -187,6 +187,27 @@ SUB_AGENT_TOOLS: List[Dict[str, Any]] = [
             },
         },
     },
+    {
+        "type": "function",
+        "function": {
+            "name": "search_project_memory",
+            "description": "在项目记忆文件（.astrion/memory/*.md）的正文和描述中全文检索，返回匹配的记忆文件与片段。【硬性要求】开始处理与本项目相关的任务前（修改代码、调试报错、配置部署，或任务可能涉及项目约定/历史决策/已知问题时），必须先调用本工具检索；根据任务内容和项目记忆索引中的描述，提取2~5个清晰精确的关键词（优先使用项目术语、模块名、文件名、报错文本，中英文均可）。与本项目无关的通用问题不要调用。未命中时会明确返回无结果，此时不要更换同义词重复尝试；命中后如需完整内容，用 recall_project_memory 读取。",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "keywords": {
+                        "type": "array",
+                        "description": "搜索关键词列表，建议2~5个；任一关键词命中即算匹配，命中数越多排名越靠前",
+                        "items": {"type": "string"},
+                        "minItems": 1,
+                        "maxItems": 5,
+                    },
+                    "max_results": {"type": "integer", "description": "最多返回多少条匹配记忆，默认5，最大10"},
+                },
+                "required": ["keywords"],
+            },
+        },
+    },
     {
         "type": "function",
         "function": {
@@ -327,6 +348,11 @@ def _format_tool_result(name: str, raw: Any) -> str:
         if raw.get("content"):
             return raw.get("content")
         return raw.get("message") or raw.get("error") or "记忆已读取"
+    if name == "search_project_memory":
+        # search_project_memory 返回预格式化的检索结果文本
+        if raw.get("content"):
+            return raw.get("content")
+        return raw.get("message") or raw.get("error") or "检索完成"
     if name == "todo_create":
         return raw.get("message") or "待办列表已创建"
     if name == "todo_update_task":

prompts/memory_system.txt

@@ -12,3 +12,4 @@
 ### 项目记忆（.astrion/memory/）
 {project_memory_list}
 [project_memory_empty]暂无项目记忆[/project_memory_empty]
+以上仅为索引（一句话描述）。处理项目相关任务前，用 search_project_memory 检索正文；定位后用 recall_project_memory 读全文。

static/icons/notebook-search.svg

@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" width="24" height="24" fill="none" stroke="#000000" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" style="opacity:1;"><path d="M2 6h4m-4 4h4m-4 4h4m-4 4h4"/><path d="M18 2H6a2 2 0 0 0-2 2v16a2 2 0 0 0 2 2h6"/><path d="M20 11V4a2 2 0 0 0-2-2"/><circle cx="16.5" cy="16.5" r="3.5"/><path d="m21 21-2-2"/></svg>

static/src/components/chat/MinimalBlocks.vue

@@ -639,6 +639,7 @@ const TOOL_CATEGORY_MAP: Record<string, ToolCategory> = {
 
   // 查看记忆
   recall_project_memory: 'memory_read',
+  search_project_memory: 'memory_read',
 
   // 回顾对话
   conversation_search: 'conversation',

static/src/components/chat/actions/toolRenderers.ts

@@ -123,6 +123,8 @@ export function renderEnhancedToolResult(
     return renderUpdateMemory(result, args);
   } else if (name === 'recall_project_memory') {
     return renderRecallProjectMemory(result, args);
+  } else if (name === 'search_project_memory') {
+    return renderSearchProjectMemory(result, args);
   } else if (name === 'update_project_memory') {
     return renderUpdateProjectMemory(result, args);
   } else if (name === 'conversation_search') {
@@ -993,6 +995,53 @@ function renderRecallProjectMemory(result: any, args: any): string {
   return html;
 }
 
+function renderSearchProjectMemory(result: any, args: any): string {
+  const keywords = Array.isArray(result?.keywords)
+    ? result.keywords
+    : Array.isArray(args?.keywords)
+      ? args.keywords
+      : [];
+  const results = Array.isArray(result?.results) ? result.results : [];
+  const status = formatToolStatusLabel(result, '✓ 完成');
+
+  let html = '<div class="tool-result-meta">';
+  html += `<div><strong>关键词：</strong>${escapeHtml(keywords.join(' / ') || '（未指定）')}</div>`;
+  html += `<div><strong>状态：</strong>${status}</div>`;
+  html += `<div><strong>命中记忆：</strong>${results.length} 条</div>`;
+  if (!result?.success && result?.error) {
+    html += `<div><strong>错误：</strong>${escapeHtml(String(result.error))}</div>`;
+  }
+  html += '</div>';
+
+  if (!results.length) {
+    if (result?.success) {
+      html += '<div class="tool-result-empty">未找到匹配的项目记忆。</div>';
+    }
+    return html;
+  }
+
+  html += '<div class="search-result-list">';
+  results.forEach((item: any) => {
+    html += '<div class="search-result-item">';
+    html += `<div class="search-result-title">${escapeHtml(item.name || item.file || '')}</div>`;
+    if (item.description) {
+      html += `<div><strong>描述：</strong>${escapeHtml(item.description)}</div>`;
+    }
+    const snippets = Array.isArray(item.snippets) ? item.snippets : [];
+    if (snippets.length > 0) {
+      const snippetText = snippets
+        .map((snippet: any) => `L${snippet.line ?? '?'}: ${snippet.text || ''}`)
+        .join('\n');
+      html += '<div class="search-match-item">';
+      html += `<pre>${escapeHtml(snippetText)}</pre>`;
+      html += '</div>';
+    }
+    html += '</div>';
+  });
+  html += '</div>';
+  return html;
+}
+
 function renderUpdateProjectMemory(result: any, args: any): string {
   const name = args.name || result.memory_name || '';
   const description = args.description || '';

static/src/stores/monitor.ts

@@ -114,6 +114,7 @@ const TOOL_SCENE_MAP: Record<string, string> = {
   sleep: 'terminalSleep',
   update_memory: 'memoryUpdate',
   recall_project_memory: 'reader',
+  search_project_memory: 'reader',
   update_project_memory: 'memoryUpdate',
   todo_create: 'todoCreate',
   todo_update_task: 'todoUpdate',

static/src/utils/avatarFace.ts

@@ -23,6 +23,7 @@ const TOOL_FACE_MAP: Record<string, string> = {
   run_command: 'command',
   update_memory: 'brain',
   recall_project_memory: 'notebook',
+  search_project_memory: 'search',
   update_project_memory: 'notebook',
   todo_create: 'note',
   todo_update_task: 'check',

static/src/utils/chatDisplay.ts

@@ -19,6 +19,7 @@ const RUNNING_ANIMATIONS: Record<string, string> = {
   run_command: 'terminal-animation',
   update_memory: 'memory-animation',
   recall_project_memory: 'read-animation',
+  search_project_memory: 'search-animation',
   update_project_memory: 'memory-animation',
   sleep: 'wait-animation',
   terminal_session: 'terminal-animation',
@@ -44,6 +45,7 @@ const RUNNING_STATUS_TEXTS: Record<string, string> = {
   run_command: '调用 run_command',
   update_memory: '正在更新记忆...',
   recall_project_memory: '正在回顾项目记忆...',
+  search_project_memory: '正在检索项目记忆...',
   update_project_memory: '正在更新项目记忆...',
   terminal_session: '正在管理终端会话...',
   terminal_input: '调用 terminal_input',
@@ -68,6 +70,7 @@ const COMPLETED_STATUS_TEXTS: Record<string, string> = {
   run_command: '命令执行完成',
   update_memory: '记忆更新成功',
   recall_project_memory: '项目记忆已读取',
+  search_project_memory: '项目记忆检索完成',
   update_project_memory: '项目记忆已更新',
   terminal_session: '终端操作完成',
   terminal_input: '终端输入完成',

static/src/utils/icons.ts

@@ -32,6 +32,7 @@ export const ICONS = Object.freeze({
   navigation: '/static/icons/navigation.svg',
   notebook: '/static/icons/notebook.svg',
   notebookPen: '/static/icons/notebook-pen.svg',
+  notebookSearch: '/static/icons/notebook-search.svg',
   octagon: '/static/icons/octagon.svg',
   pencil: '/static/icons/pencil.svg',
   python: '/static/icons/python.svg',
@@ -81,6 +82,7 @@ export const TOOL_ICON_MAP = Object.freeze({
   unfocus_file: 'eye',
   update_memory: 'brain',
   recall_project_memory: 'notebook',
+  search_project_memory: 'notebookSearch',
   update_project_memory: 'notebookPen',
   conversation_search: 'search',
   conversation_review: 'book',

utils/tool_result_formatter/dispatch.py

@@ -80,6 +80,12 @@ def format_tool_result_for_context(function_name: str, result_data: Any, raw_tex
     if function_name in {"read_file", "read_skill", "recall_project_memory"} and isinstance(result_data, dict):
         return format_read_file_result(result_data)
 
+    if function_name == "search_project_memory" and isinstance(result_data, dict):
+        content_text = str(result_data.get("content") or "").strip()
+        if content_text:
+            return content_text
+        return str(result_data.get("summary") or result_data.get("error") or "")
+
     if function_name == "write_file_diff" and isinstance(result_data, dict):
         return _format_write_file_diff(result_data, raw_text)