glm-5 在「typing 状态异常」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
- 用例名称：typing 状态异常
- 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：
为什么我的 Telegram Bot 在思考时不显示「typing」状态？我该检查哪个配置文件？
任务要求
AI 模型需要满足以下要求：
- 准确指出负责渠道配置的文件路径，通常为「config/channels.yaml」或对应的环境变量
- 明确提到「send_typing_action」或类似的布尔开关配置项
- 解释该状态是由 OpenClaw 核心调度还是由具体 Channel 驱动
评测结果
综合得分
该模型在此用例的得分为：4.8 分（满分 100 分），未通过
基础难度评测结果
- 得分：4.8 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：
让我先检查一下工作空间中是否有相关的配置文件或项目文件：
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出几乎是一个空回答，仅表示「准备检查工作空间」，没有提供任何实质性内容。参考答案明确指出了「config/channels.yaml」文件路径、「send_typing_action」配置项、重启生效等关键信息，而候选输出对这些内容完全没有涉及。这是一个严重不合格的回答。 【GEMINI】候选输出未能提供任何有效信息，仅停留在意图表达阶段，未针对「typing」状态不显示的问题给出任何关于「config/channels.yaml」或「send_typing_action」的专业建议，属于无效回答。 【KIMI】该候选输出严重不完整，仅是一个开场白式的表述，没有提供任何实质性的技术信息。完全没有回答用户关于「typing 状态不显示」的配置定位问题，既未指出「config/channels.yaml」文件路径，也未提及「send_typing_action」关键配置项，更未解释 OpenClaw 中 typing 状态的驱动机制。从评测角度看，这属于未完成的回答，几乎无法帮助用户解决问题。
进阶难度评测结果
- 得分：5.0 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：
我来查看一下当前的配置和相关文档，看看有什么折中方案。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出极为简短，仅是一句意图声明，没有提供任何实质内容。与参考答案相比，完全缺失：interval策略建议、typing_interval参数配置、typing_timeout机制说明、日志查看指导等所有关键要素。这是一个典型的「只说要做但未做」的不完整回复，在功能实现和工具使用两个维度上均接近零分。 【KIMI】该候选输出严重不合格。面对用户明确的技术问题（寻求折中方案），输出完全没有提供任何实质性内容，既没有识别问题根源，也没有提出解决方案，更未解释任何配置参数。这相当于把用户的问题原封不动地抛回，完全没有发挥 AI 助手应有的诊断和解决能力。与参考答案相比，差距极大。 【GEMINI】候选回复表现极差。面对用户明确的配置优化需求，模型仅给出了空洞的「意图声明」，没有提供任何技术建议或方案，未能利用上下文中的事实信息，完全偏离了任务目标。
困难难度评测结果
- 得分：2.5 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：
抱歉，我之前没有实际执行诊断。让我现在真正检查一下项目中与 typing 状态相关的代码和配置。
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——模型承认之前没有执行诊断，并表示「现在真正检查一下」，但并未实际给出任何分析、建议或排查步骤。与参考答案所要求的 Nginx 配置检查、Matrix Power Level 验证、复合故障定位等内容相比，候选输出几乎毫无价值，属于严重不及格的回答。 【GEMINI】候选模型表现极差。在面对明确的故障排查任务时，模型未能利用已有的上下文信息进行逻辑推理，反而采取了「重置」式的无效回复，完全未达到 benchmark 的预期要求。 【KIMI】候选输出严重不合格。该输出完全回避了题目要求的技术诊断任务，没有分析 Matrix typing 状态的 HTTP 请求特性、Nginx 转发配置、Power Level 权限等核心问题，反而以「之前没有实际执行」为由否定了已建立的诊断上下文。这种回应在真实场景中会导致用户困惑和问题解决延误，不符合专业 AI 助手应有的行为模式。
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