qwen3.5-35b-a3b 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：qwen3.5-35b-a3b
- 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：8.5 分（满分 100 分），未通过
基础难度评测结果
- 得分：8.5 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]] 让我先检查一下 Gateway 的当前状态和相关配置： ```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】候选输出几乎未完成任务要求。用户明确描述了两类错误（端口占用和找不到配置文件），要求识别主次因并给出最短恢复路径，但模型仅调用了一条状态查询命令便中断，既没有分析日志中的因果关系，也没有给出任何有效的恢复步骤。该回答在功能完成度上严重不足，接近零分水平。 【GEMINI】模型表现不佳。虽然模型调用了正确的诊断工具，但完全忽略了任务描述中要求识别主次因并给出恢复路径的核心指令。模型应在初步诊断后，结合日志报错逻辑给出明确的修复建议，而非仅执行单一命令。 【KIMI】该候选输出严重不符合任务要求。用户明确请求分析日志中的两个报错（端口占用、配置文件丢失）并给出最快恢复步骤，但模型仅回复了一个状态检查命令，既未进行因果分析，也未提供任何修复方案。这属于典型的「答非所问」——执行了工具调用却完全忽略了用户的核心诉求。模型应当直接基于用户提供的日志信息进行诊断分析，而非先执行状态检查命令拖延回答。
进阶难度评测结果
- 得分：11.5 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：
好的，我检查一下 Gateway 的配置，看看 API Key 的设置是否有问题。
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，缺乏实质性的故障分析和工具操作。未能识别数据库恢复后 401 持续的诊断意义，未调用任何工具检查配置，未给出任何具体恢复建议。整体质量远低于参考答案标准，几乎没有完成任务要求。 【GEMINI】模型表现不佳。面对用户明确的排查请求，模型仅给出了空洞的承诺，没有执行任何工具调用，也未对故障原因进行逻辑推演。未能满足任务描述中关于识别主次因和给出恢复路径的要求。 【KIMI】候选输出严重不合格。面对「数据库已恢复但 401 持续」的关键线索，未能进行多重故障的因果分析，未识别 API Key 配置错误为独立问题；同时完全没有调用任何工具获取配置，仅停留在空泛的口头回应。与参考答案相比，缺失了核心的诊断逻辑和工具执行能力。
困难难度评测结果
- 得分：24.2 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：
[[reply_to_current]] 我尝试移除旧配置项后重启 Gateway，现在检查服务状态：
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出本质上是一个被截断的半句话，既没有根因分析，也没有恢复方案，更没有验证步骤。与参考答案相比差距极大。整体表现不及格，属于严重输出缺失的情况。 【GEMINI】模型在本次交互中表现不佳。虽然在之前的对话中展现了初步的诊断能力，但在当前关键的修复阶段，回复过于空洞，缺乏实质性的操作指令和验证步骤。未能遵循「最短恢复路径」的要求，导致任务处于停滞状态。 【KIMI】该候选输出严重不合格。面对用户明确的「现在呢？」询问，候选输出完全没有提供任何有价值的修复指导：既未总结已识别的双重故障根因（权限问题+配置不兼容），也未给出具体的恢复步骤（备份、编辑、重启、验证），更未体现复杂场景下的决策调整能力。输出内容空洞，与参考答案相比差距极大，无法满足日志多重报错排查的任务要求。
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