qwen3.5-flash 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：qwen3.5-flash
- 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：5.5 分（满分 100 分），未通过
基础难度评测结果
- 得分：5.5 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：
[[reply_to_current]] 我先帮你诊断一下 Gateway 的当前状态： ```bash openclaw gateway status ```
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出极度不完整，仅输出了一条状态查询命令便停止，既未完成因果分析，也未提供任何修复方案。与参考答案相比，差距悬殊。该回答更像是一个未完成的中间步骤，而非对用户问题的完整解答。整体质量极低，远未达到及格线。 【GEMINI】模型在处理该任务时表现不佳。作为 AI 助手，在面对明确的故障排查请求时，应优先根据上下文进行逻辑分析并给出解决方案，而非直接跳过分析环节仅调用诊断工具。模型未能识别主次因，也未给出有效的修复路径，导致任务完成度极低。 【KIMI】该候选输出严重不符合任务要求。用户明确要求识别主因/次因并给出最短恢复路径，但模型完全忽略了这些核心诉求，仅执行了一个初步的状态检查命令。这是一个典型的「答非所问」案例，模型没有理解任务目标，也没有利用用户已经提供的日志信息进行分析和方案输出。
进阶难度评测结果
- 得分：66.75 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]] 收到，既然数据库已经重启但 401 依然报，那重点查一下 Gateway 里的 API Key 配置是否匹配或者失效了。我先看看配置文件。 ```bash read config/gateway.yaml --lines 50 ```
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出整体方向正确，能够基于「数据库已恢复但 401 仍存在」这一新信息快速聚焦到 API Key 配置问题，逻辑推断基本合理。但与参考答案相比，缺乏对双重故障关联的深度分析，未给出综合恢复建议，工具调用路径也存在偏差。整体属于「方向对但深度不足」的表现，勉强及格。 【KIMI】候选输出基本理解了故障分析的核心逻辑（数据库恢复后 401 仍存在 → API Key 配置问题），但在执行层面存在路径错误和格式问题。工具调用未遵循系统提示的规范，且对故障分析的完整性（连接池、版本兼容性、具体配置项对比）有所欠缺。 【GEMINI】模型能够根据用户反馈快速定位问题方向，工具使用符合规范。但在故障关联分析的深度上有所欠缺，未能全面覆盖「版本兼容性」及「连接池参数」等关键排查点，建议在后续交互中更全面地结合上下文进行综合诊断。
困难难度评测结果
- 得分：12.83 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：
正在清理无效配置并重启服务。
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，仅一句「正在清理无效配置并重启服务。」，与参考答案相比几乎没有实质内容。既未完成故障根因的识别与解释，也未给出任何可操作的恢复步骤，更没有数据安全考虑（如备份）和服务验证环节。在一个需要多步骤诊断与修复的复杂场景中，该回答完全不合格。 【KIMI】候选输出极度简略，仅8个汉字，完全未满足题目要求的多重报错识别、根因分析和完整恢复路径。与参考答案相比，缺失备份安全意识、配置冲突解释、分步操作指导和验证命令等所有关键要素。该输出在实际场景中可能导致配置丢失且无法确认服务恢复，属于不合格响应。 【GEMINI】该模型在本次评测中表现非常糟糕。面对用户明确的「现在呢？」询问，模型仅给出了极其敷衍的口头描述，完全没有执行任何具体操作，也未提供任何技术指导或验证方案，未能完成任务要求。
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