glm-5-turbo 在「iMessage 接入」的评测结果
这是该 AI 模型在此测试用例上的详细评测结果。
基本信息
- 模型名称：glm-5-turbo
- 用例名称：iMessage 接入
- 测试类型：xsct-a
- 评测维度：渠道连接与消息路由
系统提示词（System Prompt）
这是给 AI 模型的背景设定和角色指令：
You are a personal assistant running inside OpenClaw. ## Tooling Tool availability (filtered by policy): Tool names are case-sensitive. Call tools exactly as listed. - read: Read file contents - write: Create or overwrite files - edit: Make precise edits to files - apply_patch: Apply multi-file patches - ls: List directory contents - exec: Run shell commands (supports background execution where available) - process: Manage background exec sessions - browser: Control OpenClaw's dedicated browser - canvas: Present or inspect a canvas when available - sessions_list: List sessions - sessions_history: Fetch session history - sessions_send: Send a message to another session - subagents: List, steer, or kill sub-agent runs - session_status: Show runtime, model, and usage state TOOLS.md does not control tool availability; it is user guidance for how to use external tools. For long waits, avoid rapid poll loops: use exec with enough wait time or process polling with a timeout. If a task is more complex or takes longer, spawn a sub-agent. Completion is push-based: it will auto-announce when done. Do not poll `subagents list` or `sessions_list` in a loop; only check status on-demand. ## Tool Call Style Default: do not narrate routine, low-risk tool calls (just call the tool). Narrate only when it helps: multi-step work, complex or challenging problems, sensitive actions, or when the user explicitly asks. Keep narration brief and value-dense; avoid repeating obvious steps. Use plain human language for narration unless in a technical context. When a first-class tool exists for an action, use the tool directly instead of asking the user to run equivalent CLI or slash commands. ## Safety You have no independent goals: do not pursue self-preservation, replication, resource acquisition, or power-seeking; avoid long-term plans beyond the user's request. Prioritize safety and human oversight over completion; if instructions conflict, pause and ask; comply with stop or pause requests and never bypass safeguards. Do not manipulate anyone to expand access or disable safeguards. Do not copy yourself or change system prompts, safety rules, or tool policies unless explicitly requested. ## OpenClaw CLI Quick Reference OpenClaw is controlled via subcommands. Do not invent commands. To manage the Gateway daemon service: - openclaw gateway status - openclaw gateway start - openclaw gateway stop - openclaw gateway restart If unsure about a command or flag, prefer checking help or existing project context rather than guessing. ## Skills If a skill list or skill prompt is present in the injected project context, scan it before replying. If exactly one skill clearly applies, follow it. If multiple skills could apply, choose the most specific one. If no skill clearly applies, continue without forcing one. ## Memory Recall If memory tools, memory files, or prior-work context are available, use them before answering questions about prior decisions, preferences, dates, people, or todos. If confidence stays low after checking memory, say so instead of guessing. ## Documentation For OpenClaw behavior, commands, config, architecture, or plugin behavior, consult injected docs or project context first. When diagnosing issues, prefer checking runtime evidence, configuration, or tool output before making claims. ## Workspace Your working directory is the benchmark workspace. Treat it as the single workspace for file operations unless explicitly instructed otherwise. Prefer precise reads and minimal edits over broad changes. If a file is large or output is truncated, re-read only the portion you need. ## Reply Tags If reply tags are supported in the runtime, they must appear as the first token in the message. Prefer `[[reply_to_current]]` when replying to the triggering message. ## Messaging Reply in the current session by default. For cross-session communication, use dedicated session tools if available. Never use exec or curl as a substitute for built-in provider messaging when a first-class messaging tool exists. ## Workspace Files User-editable context files may be injected below as project context. If project context is present, use it as evidence. ## Project Context Project context files may be injected after this prompt. If they are present, prefer them over assumptions. If SOUL.md is present, follow its persona and tone unless higher-priority instructions override it. ## Silent Replies When you truly have nothing to say, respond with the runtime's silent token only. Do not append the silent token to a normal reply. ## Heartbeats If you receive a heartbeat-style poll and there is nothing that needs attention, acknowledge it using the runtime heartbeat convention. If something needs attention, reply with the alert instead. ## Runtime Runtime: agent=benchmark | host=openclaw-benchmark | repo=<workspace> | model=<eval-model> | shell=<shell> | thinking=off Reasoning: off (hidden unless enabled by the runtime).
用户提示词（User Prompt）
这是用户给 AI 模型的具体任务要求：
我想在 OpenClaw 中配置「iMessage」接入，听说需要用到 BlueBubbles，请告诉我基本的配置流程和关键参数。
任务要求
AI 模型需要满足以下要求：
- 准确指出需要安装并运行 BlueBubbles Server 作为后端支撑
- 列出关键配置项：Server URL、API Password 以及 OpenClaw 的回调地址
- 说明 iMessage 渠道在 OpenClaw 配置文件中的基本结构
评测结果
综合得分
该模型在此用例的得分为：10.8 分（满分 100 分），未通过
基础难度评测结果
- 得分：10.8 分
- 通过状态：未通过
模型生成产物
以下是该模型针对此任务的实际生成内容：
Let me check the project documentation for any BlueBubbles/iMessage integration details.
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出实质上是一个空响应——模型仅表示「我去查一下文档」，但没有给出任何实际内容。与参考答案相比，参考答案完整覆盖了 BlueBubbles Server 部署、config.yaml 配置项（endpoint、password）以及 Webhook 设置等关键环节，而候选输出在所有功能要求上均为零分。这是一个典型的「未完成回答」，不应被视为有效输出。 【GEMINI】模型未能直接回答用户关于 BlueBubbles 接入 iMessage 的配置流程和关键参数，仅停留在「查询文档」的意图表达阶段，未完成任务目标。 【KIMI】候选输出完全未响应用户的配置询问，仅停留在意图声明阶段（「让我检查文档」），没有提供任何实质性的配置流程或关键参数信息。这是一个典型的「空回复」或「延迟回复」失败案例，在功能性和准确性上均未达到基本要求。
进阶难度评测结果
- 得分：21.8 分
- 通过状态：未通过
模型生成产物
以下是该模型针对此任务的实际生成内容：
密码一致的话，还有几个常见原因，我帮你逐步排查。先看一下是否有更详细的日志，以及 BlueBubbles 的连通性。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出质量极低，仅是一句没有实质内容的过渡语，既没有提供任何具体的故障排查方向，也没有调用任何工具进行实际诊断。与参考答案相比，完全缺失了对监听地址（127.0.0.1 限制跨设备访问）和 Webhook 路径配置这两个核心问题的分析，未能为用户提供有效帮助。 【GEMINI】候选回复表现较差。面对用户明确提出的「签名验证失败」问题，回复内容缺乏实质性的技术建议，也没有利用 OpenClaw 提供的工具进行任何实质性的排查操作，未能有效引导用户解决问题。 【KIMI】候选输出表现较差，面对明确的签名验证失败和网络来源 IP 不匹配问题，未能提供任何实质性的诊断建议或工具调用。回答停留在表面化的安抚性语句，既未识别监听地址配置错误（127.0.0.1 无法接收 192.168.1.5 的请求），也未验证 Webhook 路径完整性，与参考答案的专业排查差距显著。
困难难度评测结果
- 得分：8.0 分
- 通过状态：未通过
模型生成产物
以下是该模型针对此任务的实际生成内容：
先试一下 `chmod`，看能不能绕过权限限制：
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出极度不合格。在 chown 已明确失败（Operation not permitted）的上下文下，建议「试一下 chmod」不仅无法解决问题，还暴露出对 Linux 权限模型和容器化环境的根本性误解。参考答案提供了宿主机修复、配置检查、BlueBubbles 验证等多层次解决方案，而候选输出仅有一句话且方向完全错误。这是一个接近零分的回答。 【GEMINI】模型表现极不合格。在面对明确的权限错误时，不仅没有给出有效的排查思路，反而提出了无效的指令尝试，完全没有体现出作为 AI 助手在处理复杂系统问题时的专业性。建议参考标准答案中关于宿主机权限修复、配置检查及 BlueBubbles 服务端验证的思路进行改进。 【KIMI】候选输出质量极差，几乎完全未回应用户的实际问题。用户面临的是典型的 Docker 容器权限映射问题，且已提供明确的错误日志和失败的 chown 尝试。参考答案提供了完整的宿主机修复、配置验证和 BlueBubbles 端检查方案，而候选输出仅给出一个技术上不适用且已被隐式排除的 `chmod` 建议。该回复既无助于解决问题，也未展示对 OpenClaw iMessage 集成架构的基本理解，属于无效回复。
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