feat: FC 工具去重 + 按场景动态裁剪，降低 AI 每轮负担

方案 A（去重）: - mcp_to_openai_tools 末尾按 function.name 去重，消除 cache+builtin 叠加造成的同名重复（memory/scheduler/lsp__* 等），FC 工具 42→36，去掉约 14% 的垃圾 schema token - get_liugin_usage_prompts 的 plugins 段由逐条 name:desc 改为工具名清单，消除与 FC tools 字段的双重曝光，保留无 FC 模型的回退清单方案 B（分层裁剪）: - 新增 prune_tools(fc_tools, user_input): 常驻 ALWAYS(tool_search/memory/ scheduler) + 外部桥接(mcp__)默认保留 + 按关键词信号追加对应工具 (代码/文件->code_editor+file_manager+lsp__*; git/shell/浏览器/搜索/子agent/ 工程化各按信号) - cli_core 两处 FC 构建点(TUI/CLI)接入 prune_tools(current_input) 实测(AICLI): 纯聊天 FC token ~4310->285(降93%)，写代码 ~973(降77%) 测试: 新增 tests/test_prune_tools.py (7 passed)，全量 324 passed 无回归
2026-08-06 20:06:51 +08:00
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+"""
+测试：FC 工具去重 + 按场景动态裁剪（方案 A+B）。
+
+不依赖真实插件/引擎加载，用构造的 fake 数据验证：
+- mcp_to_openai_tools 按 name 去重（消除 cache + builtin 叠加重复）
+- prune_tools 分层裁剪：纯聊天极简、代码信号追加 lsp__*、外部 mcp 默认保留
+"""
+import pytest
+
+from xcli_core.fc_tools import mcp_to_openai_tools, prune_tools
+
+
+def _fc(name, desc="d"):
+    return {
+        "type": "function",
+        "function": {
+            "name": name,
+            "description": desc,
+            "parameters": {"type": "object", "properties": {}, "required": []},
+        },
+    }
+
+
+def _mcp(name, desc="d"):
+    """MCP 格式（get_mcp_tools 返回的就是这种）"""
+    return {
+        "name": name,
+        "description": desc,
+        "inputSchema": {"type": "object", "properties": {}, "required": []},
+    }
+
+
+class _FakePM:
+    """最小 plugin_manager：get_mcp_tools 返回预置列表。"""
+
+    def __init__(self, tools):
+        self._tools = tools
+
+    def get_mcp_tools(self):
+        return self._tools
+
+
+# ───────────── 去重 ─────────────
+
+def test_mcp_to_openai_tools_dedup():
+    # 模拟真实场景：cache 里已有 memory/scheduler，_get_builtin_tools 又追加一遍
+    pm = _FakePM([
+        _mcp("a"), _mcp("a"),                     # 同名重复
+        _mcp("b"),
+        _mcp("memory"), _mcp("scheduler"),        # cache 已有
+    ])
+    out = mcp_to_openai_tools(pm)
+    names = [t["function"]["name"] for t in out]
+    assert names.count("a") == 1, "同名工具应去重为 1"
+    assert names.count("memory") == 1, "builtin 与 cache 重复应去重"
+    assert names.count("scheduler") == 1
+    assert "b" in names
+    # builtin 追加的 memory/scheduler 不应再产生第二份
+    assert names.count("memory") == 1
+
+
+# ───────────── 分层裁剪 ─────────────
+
+_CORE = ["tool_search", "memory", "scheduler", "code_editor", "code_search",
+         "file_manager", "lsp__diagnostics", "lsp__hover", "lsp__definition",
+         "lsp__references", "lsp__completion", "browser_auto", "network_tools",
+         "ai_search", "git_tools", "cmd_executor", "sub_agent", "auto_engineer"]
+
+
+def _full_set():
+    return [_fc(n) for n in _CORE]
+
+
+def test_prune_pure_chat_keeps_only_always():
+    out = prune_tools(_full_set(), "你好啊，今天天气真不错")
+    names = {t["function"]["name"] for t in out}
+    assert names == {"tool_search", "memory", "scheduler"}, \
+        f"纯聊天应只留常驻工具，实际: {names}"
+
+
+def test_prune_code_signal_adds_lsp():
+    out = prune_tools(_full_set(), "帮我写一个 python 脚本读取文件")
+    names = {t["function"]["name"] for t in out}
+    assert "code_editor" in names
+    assert "file_manager" in names
+    assert "lsp__diagnostics" in names, "写代码应追加 pylsp 的 lsp__* 工具"
+    assert "lsp__completion" in names
+    assert "tool_search" in names
+
+
+def test_prune_git_signal():
+    out = prune_tools(_full_set(), "提交代码并查看 git 状态")
+    names = {t["function"]["name"] for t in out}
+    assert "git_tools" in names
+    assert "tool_search" in names
+
+
+def test_prune_external_mcp_kept_even_in_chat():
+    tools = [_fc("my_mcp__search"), _fc("code_editor"), _fc("tool_search")]
+    out = prune_tools(tools, "你好")
+    names = {t["function"]["name"] for t in out}
+    assert "my_mcp__search" in names, "外部桥接工具(mcp__)应默认保留"
+    assert "code_editor" not in names, "未命中信号的低频工具应被裁剪"
+    assert "tool_search" in names
+
+
+def test_prune_empty_input_no_crash():
+    out = prune_tools(_full_set(), "")
+    names = {t["function"]["name"] for t in out}
+    assert names == {"tool_search", "memory", "scheduler"}
+
+
+def test_prune_none_tools_returns_none():
+    assert prune_tools(None, "任意输入") is None
+    assert prune_tools([], "任意输入") == []