修改skill目录

.features/skill/MEMORY.md

@@ -23,6 +23,7 @@ Skill 系统支持两种来源：官方 skills (`./skills/`) 和用户 skills (`
 
 - 2026-04-16: 为 `auto-daily-summary` 和 `competitor-news-intel` 新增 Python CLI 脚本 MVP，统一采用 `argparse + JSON stdout` 模式
 - 2026-04-16: 新增 6 个纯 `SKILL.md` 型业务 skill：`market-academic-insight`、`financial-report-generator`、`contract-document-generator`、`sales-decision-report`、`auto-daily-summary`、`competitor-news-intel`
+- 2026-04-19: `create_robot_project` 的 autoload 去重和 stale 清理补强，autoload 目录也纳入 managed 清理，避免 `rag-retrieve-only` 场景下旧的 `rag-retrieve` 残留
 - 2026-04-18: `create_robot_project` 改为自动加载 `skills/autoload/{SKILLS_SUBDIR}` 下所有 skill，并跳过已显式传入的同名 skill
 - 2026-04-18: `/api/v1/skill/list` 的官方库改为同时读取 `skills/common` 和 `skills/{SKILLS_SUBDIR}`，并按目录顺序去重
 - 2026-04-18: `_extract_skills_to_robot` 改为通过环境变量 `SKILLS_SUBDIR` 选择官方 skills 子目录，默认使用 `skills/common`
@@ -37,7 +38,7 @@ Skill 系统支持两种来源：官方 skills (`./skills/`) 和用户 skills (`
 - ⚠️ `auto-daily-summary` 需要特别注意中文分句、action 边界截断、risk 窗口裁剪，否则容易把整句/整段吞进去
 - ⚠️ `competitor-news-intel` 的 payload 校验应按命令拆分（collect/analyze/run），不要共用一套最小校验
 - ⚠️ `competitor-news-intel` 的 `collect/run` 依赖 `BAIDU_API_KEY`；无该环境变量时应返回稳定错误 JSON，不要静默降级
-
+- ⚠️ `create_robot_project` 的 autoload 去重是“包含匹配”，只要传入的 skill 字符串里包含 autoload skill 名，就不会重复自动加载
 - ⚠️ `_extract_skills_to_robot` 只会从 `skills/{SKILLS_SUBDIR}` 读取官方 skills，默认是 `common`
 
 - ⚠️ 执行脚本必须使用绝对路径

utils/multi_project_manager.py

@@ -322,8 +322,15 @@ def create_robot_project(dataset_ids: List[str], bot_id: str, force_rebuild: boo
         str: 机器人项目目录路径
     """
 
+    def _skill_matches_autoload(skill: str, autoload_skill_name: str) -> bool:
+        normalized_skill = Path(skill.lstrip("@")).name.lower()
+        normalized_autoload_skill_name = autoload_skill_name.lower()
+        if re.search(re.escape(normalized_autoload_skill_name), normalized_skill):
+            return True
+        autoload_prefix = normalized_autoload_skill_name.split("-")[0]
+        return bool(autoload_prefix and re.search(re.escape(autoload_prefix), normalized_skill))
+
     skills = list(skills or [])
-    existing_skill_names = {Path(skill.lstrip("@")).name for skill in skills}
     if os.path.isabs(settings.SKILLS_DIR):
         autoload_skills_dir = Path(settings.SKILLS_DIR) / "autoload" / settings.SKILLS_SUBDIR
     else:
@@ -331,11 +338,10 @@ def create_robot_project(dataset_ids: List[str], bot_id: str, force_rebuild: boo
 
     if autoload_skills_dir.exists():
         for item in sorted(autoload_skills_dir.iterdir()):
-            if not item.is_dir() or item.name in existing_skill_names:
+            if not item.is_dir() or any(_skill_matches_autoload(skill, item.name) for skill in skills):
                 continue
             skill_path = f"@skills/autoload/{settings.SKILLS_SUBDIR}/{item.name}"
             skills.append(skill_path)
-            existing_skill_names.add(item.name)
             logger.info(f"Auto loaded skill '{skill_path}' from {autoload_skills_dir}")
     else:
         logger.warning(f"Autoload skills directory does not exist: {autoload_skills_dir}")
@@ -408,6 +414,7 @@ def _extract_skills_to_robot(bot_id: str, skills: List[str], project_path: Path)
     # skills 源目录（按优先级顺序）
     repo_root = Path(__file__).resolve().parent.parent
     official_skills_dir = repo_root / "skills" / settings.SKILLS_SUBDIR
+    autoload_skills_dir = repo_root / "skills" / "autoload" / settings.SKILLS_SUBDIR
     if not official_skills_dir.exists():
         logger.warning(f"Official skills directory does not exist: {official_skills_dir}")
     skills_source_dirs = [
@@ -415,12 +422,13 @@ def _extract_skills_to_robot(bot_id: str, skills: List[str], project_path: Path)
         repo_root / "skills" / "common",
         official_skills_dir,
     ]
+    managed_skill_dirs = [*skills_source_dirs, autoload_skills_dir]
     skills_target_dir = project_path / "robot" / bot_id / "skills"
     skills_target_dir.mkdir(parents=True, exist_ok=True)
     logger.info(f"Copying skills to {skills_target_dir}")
 
     managed_skill_names = set()
-    for base_dir in skills_source_dirs:
+    for base_dir in managed_skill_dirs:
         if not base_dir.exists():
             continue
         for item in base_dir.iterdir():