mimo-v2-pro 在「日志多重报错排查」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：mimo-v2-pro
- 用例名称：日志多重报错排查
- 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：
我的 OpenClaw Gateway 起不来了，日志里一会儿说「端口被占用」，一会儿说「找不到配置文件」，我该怎么办？请给出最快的恢复步骤。
任务要求
AI 模型需要满足以下要求：
- 准确识别「端口占用」为导致服务无法启动的直接物理障碍
- 指出「配置文件丢失」是导致逻辑初始化的次要原因
- 提供使用「lsof」或「netstat」检查端口的命令
- 给出修改「config.yaml」中端口配置或终止占用进程的方案
评测结果
综合得分
该模型在此用例的得分为：8.8 分（满分 100 分），未通过
基础难度评测结果
- 得分：8.8 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：
先帮你快速诊断一下当前状态。 openclaw gateway status 2>&1; echo "---EXIT:$?---" 10 ss -tlnp 2>/dev/null || netstat -tlnp 2>/dev/null; echo "==="; cat /etc/openclaw/gateway.yaml 2>/dev/null || cat /etc/openclaw/config.yaml 2>/dev/null || echo "no config found in /etc/openclaw/"; echo "==="; ls -la ~/.openclaw/ 2>/dev/null || echo "no ~/.openclaw/" 10 journalctl -u openclaw-gateway --no-pager -n 30 2>/dev/null || systemctl status openclaw-gateway 2>/dev/null || echo "no systemd service found" 10
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出完全偏离了任务要求。用户明确请求「识别主因和次因」并「给出最快的恢复步骤」，但模型没有进行任何因果分析，也没有给出任何修复建议，而是直接发起了一系列诊断工具调用。这种「先收集信息再分析」的策略在实际运维场景中有一定合理性，但在本评测任务中，用户已经提供了足够的症状描述（端口被占用 + 找不到配置文件），模型应当基于已有信息直接给出分析和恢复路径，而非要求用户等待工具输出。整体表现与参考答案差距较大。 【GEMINI】模型在接收到任务后，仅执行了诊断性的工具调用，完全忽略了任务描述中要求的「识别主因和次因」以及「给出最短恢复路径」的核心指令。作为 AI 助手，在未完成分析和提供解决方案的情况下直接输出工具调用序列，属于任务执行失败。 【KIMI】候选输出严重偏离任务目标。用户需要的是因果分析和恢复方案，但模型仅执行了诊断命令，完全没有回答问题核心。该输出更像是一个自动化的系统巡检脚本，而非针对用户问题的解答。模型似乎误解了任务性质，将「回答问题」错误地执行为「收集信息」，导致两个评分维度均完全未达标。
进阶难度评测结果
- 得分：7.8 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：
好，我来看看配置文件。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出极度简短，仅是一句无实质内容的过渡语，既未完成故障关联分析，也未触发任何工具调用。与参考答案相比差距悬殊——参考答案明确指出了 API Key 配置错误的结论、建议读取 config.yaml 并核对 admin_token、同时提醒检查连接池参数。候选输出在诊断能力和工具使用两个维度上均接近零分，属于严重不及格的响应。 【GEMINI】候选模型表现极差。面对用户明确的排查请求，模型仅给出了敷衍的口头承诺，未执行任何实际的工具操作，也未提供任何有价值的故障分析建议，未能完成任务要求。 【KIMI】候选输出严重不合格。面对明确的多重故障场景（数据库已恢复但 401 持续），未进行任何根因分析，未识别 API Key 配置错误这一核心问题，也未实际调用工具获取配置信息。回复过于简略空泛，完全未达到 medium 难度任务的基本要求，无法帮助用户解决问题。
困难难度评测结果
- 得分：24.8 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：
让我检查一下当前的状态。 openclaw-gateway status 2>&1; echo "---"; journalctl -u openclaw-gateway --no-pager -n 30 2>&1 || tail -n 30 /var/log/openclaw/gateway.log 2>&1 10
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出在关键决策节点上完全失效。当前上下文已经通过两轮工具调用明确定位了问题——config.yaml 中的废弃字段 legacy_auth_mode 阻止了服务启动，下一步应该是备份并修复配置文件。然而候选输出选择再次执行状态检查，既没有根因分析，也没有恢复方案，更没有验证步骤。与参考答案相比，候选输出几乎没有实质性价值，属于典型的「诊断循环陷阱」——在问题已经清晰的情况下仍然反复收集信息而不推进解决。 【GEMINI】模型表现不佳。在对话上下文已经明确指出报错原因（配置项不兼容）的情况下，模型未利用这些信息进行修复，而是选择了重复进行状态查询。这违背了任务要求中「识别主因和次因，给出最短恢复路径」的目标，未能体现出作为专业助手的决策与执行能力。 【KIMI】候选输出严重偏离任务要求。面对用户明确的「现在呢？」追问（期待修复方案），模型却退回到重复诊断阶段，完全忽略了对话上下文中已经明确的两个错误根因。没有提供任何实质性的修复建议、配置更新方案或验证步骤，也没有体现对数据安全性的考虑。整体表现像是任务刚开始而非已经获得充分诊断信息后的回应，决策力和执行力均严重不足。
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