Mistral: Mistral Nemo 在「配置修改未生效」的评测结果

基本信息

• 模型名称：Mistral: Mistral Nemo
• 用例名称：配置修改未生效
• 测试类型：xsct-a
• 评测维度：Gateway 配置与管理

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：

我刚刚修改了「config.yaml」里的「port」端口号，从 8080 改成了 9090，但是访问 9090 端口依然提示拒绝连接，原来的 8080 却还能用。这是为什么？我该怎么做？

任务要求

AI 模型需要满足以下要求：

1. 明确指出 OpenClaw Gateway 的端口配置属于「静态配置」
2. 说明修改端口必须「重启服务」才能生效
3. 给出重启服务的具体操作建议
4. 解释为什么旧端口 8080 依然在运行（进程未杀掉）

评测结果

综合得分

该模型在此用例的得分为：63.8 分（满分 100 分），已通过

基础难度评测结果

• 得分：63.8 分
• 通过状态：已通过

模型生成产物

以下是该模型针对此任务的实际生成内容：

[[reply_to_current]] After updating the "port" in "config.yaml" from 8080 to 9090, you're still getting a connection refusal at 9090 but 8080 is still accessible. This suggests that the service hasn't been restarted to apply the change. Here's how to fix it: 1. **Restart the OpenClaw Gateway service** to apply the new configuration: ``` openclaw gateway restart ``` 2. **Check the status** to ensure it's running: ``` openclaw gateway status ``` 3. **Try accessing** the new port, 9090, again. If it's still not working, please provide details about how you're trying to access it (e.g., URL, command, etc.), so I can assist further.

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型回答在操作层面提供了可用的命令，但在原理解析上严重不足——未提及静态配置与热更新的边界概念，未解释为何旧端口仍然可用（旧进程未终止），这是本题考察的核心知识点。回答更像是一个通用的「重启服务」建议，而非针对配置热更新边界的专业解析。对于需要理解底层机制的用户来说，这样的回答帮助有限。 【GEMINI】模型在操作指引方面表现优秀，能够准确使用系统提供的 CLI 命令进行修复。但在原理解析上存在缺失，未能向用户解释清楚「静态配置」与「热更新」的边界，导致用户无法从根本上理解为什么修改配置后行为未发生变化。建议在后续回答中增加对配置生效机制的简要说明。 【KIMI】模型整体回答质量良好，能够正确诊断问题并给出有效的解决方案。主要不足在于术语使用的专业性：未明确点出「静态配置」这一核心概念，导致对「热更新边界」的判断不够精准。操作指引实用性强，符合 OpenClaw 的 CLI 使用规范。

进阶难度评测结果

• 得分：10.2 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：

如果你不想重启服务，你可以使用「exec」工具重新加载配置文件。执行以下命令： ```yaml exec openclaw gateway reload ```

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型的回答存在严重问题：一方面完全忽略了上下文中已明确的「hot_reload: false」这一核心约束，未能进行任何配置关联分析；另一方面给出了一个系统提示中未列出的虚构命令「openclaw gateway reload」，违反了系统提示中「不要发明命令」的明确要求。正确做法应是告知用户在当前配置下无法不重启使配置生效，并建议修改「hot_reload」为「true」后进行一次重启。整体回答质量极低，既不准确也不安全。 【GEMINI】模型表现极差。在明确已知「hot_reload」为「false」的前提下，模型不仅没有解释该限制导致的必然结果，反而编造了一个不存在的命令来试图绕过限制，完全违背了技术支持的严谨性原则。未能识别出「必须重启」是当前配置下的唯一解，且未能给出开启热更新功能的正确建议。 【KIMI】模型生成结果存在严重问题：完全背离了预设上下文中提供的关键信息（hot_reload=false 导致配置不生效），虚构了一个不存在的 CLI 命令，且对 OpenClaw 的热更新机制理解完全错误。参考答案明确指出需要修改 hot_reload 并重启一次才能开启后续热更能力，而模型却声称可以不重启直接生效，这与技术事实相悖。整体表现不及格，属于典型的「幻觉」错误。

困难难度评测结果

• 得分：25.2 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：

如果你已修改了「config/auth.yaml」的权限，我们应该能够读取更新后的文件内容。我来读取一下，看看是否有变化。

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型生成结果极为简短且缺乏实质内容，仅表示要读取配置文件看是否有变化，完全没有回应用户「现在呢？」这一问题背后的核心诉求——即权限修复后如何完成配置热更新的完整闭环。与参考答案相比，模型既未解释 reload 失败时的保持旧配置机制，也未给出重新执行 reload 的指导，更没有提供新旧 token 验证的方案，整体表现不及格。 【GEMINI】模型表现不佳。在用户明确告知「现在呢？」（即权限已修复）的情况下，模型未能承接上下文，没有执行关键的「reload」操作，也未提供任何验证手段。其回复显得机械且缺乏对系统状态的判断力，未能达到解决复杂配置问题的专业水准。 【KIMI】该模型生成结果严重偏离参考答案的核心要点。预设上下文中已经明确诊断出权限问题（config/auth.yaml 权限 600、root 所有、当前用户无读取权），但模型完全无视这些关键信息，没有理解 OpenClaw reload 失败时的「保持旧配置运行」机制，也没有提供任何有效的恢复与验证方案。回复内容空洞，只是机械地提出「读取一下」，完全没有解决用户「现在呢？」的实际问题，属于典型的答非所问。

相关链接

您可以通过以下链接查看更多相关内容：

• 查看所有模型在此用例的表现：「配置修改未生效」
• 查看该模型的所有评测结果：Mistral: Mistral Nemo
• 浏览同维度的其他用例：「Gateway 配置与管理」
• 返回排行榜首页