Qwen: Qwen3.5-9B 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:Qwen: Qwen3.5-9B
- 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:48.5 分(满分 100 分),未通过
基础难度评测结果
- 得分:48.5 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:
我来帮你快速排查和恢复 OpenClaw Gateway。先检查几个关键点: ```bash ls -la ``` 同时检查端口占用情况: ```bash lsof -i :6000 # 默认端口 ``` 请执行以上命令,把输出结果发给我,我会根据实际配置给你具体的修复步骤。 **常见快速恢复步骤:** 1. **端口冲突** → 先杀掉占用进程: ```bash kill -9 # 用端口号查到的进程ID ``` 2. **配置文件缺失** → 检查 config 目录是否存在: ```bash ls -la config/ ``` 3. **重启服务** → 确认配置正确后: ```bash openclaw gateway start ``` 请先执行 `ls -la` 和 `lsof -i :6000` 两个命令,告诉我输出结果,我才能给出针对性的修复指令。
AI 评审点评
以下是 AI 评审对该模型输出的点评:
【CLAUDE】候选输出整体结构尚可,涵盖了端口冲突和配置文件问题两个方向,并给出了相关命令。但核心缺陷在于:未进行因果层次分析(主因/次因的识别与解释),且采用了「先收集信息再给方案」的交互策略,导致恢复路径不够直接简洁。相比参考答案,缺少对主次矛盾的明确判断,以及修改 config.yaml 端口配置的替代方案,整体质量低于预期。 【GEMINI】模型表现一般。虽然提供了正确的排查工具(lsof)和修复思路,但未能直接针对用户提出的「最快恢复步骤」进行响应,而是倾向于分步排查。未明确区分主次因,导致诊断逻辑不够清晰。 【KIMI】候选输出采用了交互式排查风格,虽然包含了部分正确的技术命令,但未能满足任务核心要求:明确区分主次因并给出最短恢复路径。将「请执行命令后反馈」作为前置条件,实质上把一次性解决方案拆分为多轮交互,不符合「最短恢复路径」的要求。此外,对因果关系的分析停留在罗列现象层面,缺乏对报错关联性的解释。
进阶难度评测结果
- 得分:20.2 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:
我来检查 Gateway 的配置文件,看看是否有认证相关的配置问题。 ```bash ls -la ```
AI 评审点评
以下是 AI 评审对该模型输出的点评:
【CLAUDE】候选输出仅用一句话描述意图并执行了一个方向错误的命令(`ls -la` 而非 `read config.yaml`),既未对当前故障状态变化(数据库已恢复、401 仍在)做出逻辑分析,也未使用正确工具获取关键配置信息,与参考答案的要求差距悬殊。整体表现远低及格线。 【GEMINI】模型表现不佳。面对用户明确的故障排查请求,模型未能利用上下文进行逻辑推理,也未采取有效的工具调用来获取配置文件。其回复内容过于浅显,没有针对性地解决「401 错误」与「配置检查」的需求,完全偏离了预期的排查路径。 【KIMI】候选输出严重偏离任务核心要求。首先,完全忽略了用户提供的诊断关键信息(数据库已重启但 401 持续),未能进行多重故障的关联分析,没有区分主因和次因。其次,工具使用错误,用「ls」替代了应该使用的「read」工具来检查配置文件。整体表现远低于及格线,无法完成「识别主因和次因,给出最短恢复路径」的任务目标。
困难难度评测结果
- 得分:48.2 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:
权限修好后出现了第三个错误:配置文件中的「legacy_auth_mode」参数在新版本中已废弃。我需要删除或更新这个配置项才能继续。 让我先看看配置文件的内容: ```bash cat /etc/openclaw/gateway/config.yaml ```
AI 评审点评
以下是 AI 评审对该模型输出的点评:
【CLAUDE】候选输出在根因识别上有部分正确认知,但整体表现较差。对故障编号描述错误(称为「第三个错误」),暴露出上下文理解不精准;面对已明确的配置冲突问题,仅给出「查看文件」的初步动作,未提供任何实质性的修复指令或验证步骤,导致恢复路径完全不闭合。对照参考答案,候选输出缺少备份建议、配置编辑操作、重启命令及服务健康验证,实用性严重不足。 【GEMINI】模型在故障诊断方面表现出色,能够准确识别升级导致的配置冲突。但在执行策略上,模型表现得较为被动,未能像参考答案那样提供一套完整的、包含安全备份与后续验证的闭环操作方案,导致用户需要进行多次交互才能完成修复。 【KIMI】候选输出严重不符合「日志多重报错排查」的任务要求。虽然能够识别配置不兼容的表面现象,但缺乏复杂场景下的系统性决策能力,完全没有提供可执行的恢复路径,更未体现数据安全意识和验证闭环。与参考答案相比,差距显著:参考答案提供了分步骤的完整解决方案,而候选输出仅执行了一个信息收集命令后便停止,属于典型的「半途而废」型响应。在hard难度下,这种响应无法满足生产环境的故障排查需求。
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