doubao-seed-1-6-flash 在「自定义端口后访问异常」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：doubao-seed-1-6-flash
- 用例名称：自定义端口后访问异常
- 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：
我把 OpenClaw Gateway 的端口改成 9090 了，但是访问不了，是不是还要重启什么东西？
任务要求
AI 模型需要满足以下要求：
- 明确指出需要重启「openclaw-gateway」服务或进程
- 提供修改后的访问地址示例，如「http://localhost:9090」
- 给出检查端口监听状态的命令，如「netstat」或「ss」
评测结果
综合得分
该模型在此用例的得分为：35.5 分（满分 100 分），未通过
基础难度评测结果
- 得分：35.5 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：
[{"name":"exec","parameters":{"command":"openclaw gateway restart"}}]
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型通过工具调用执行了重启命令，触及了问题的核心操作，但完全以「静默执行」方式处理，既未向用户解释操作原因，也未补充客户端地址更新和端口验证等关键后续步骤，导致配置闭环严重不完整。对于一个需要「补齐配置闭环」的任务，仅重启服务远远不够，用户仍然不知道客户端需要同步修改访问地址，也无法确认服务是否真正在新端口上监听。 【GEMINI】模型虽然准确识别了需要重启服务的需求并调用了工具，但严重缺乏对用户问题的深度理解。用户的问题在于「修改端口后访问不了」，这通常涉及服务端重启和客户端配置同步两个环节。模型忽略了客户端地址更新及端口监听验证，导致任务未闭环，属于典型的「只动手不动脑」的执行模式。 【KIMI】模型过度依赖「默认不叙述低风险工具调用」的规则，将本需多步骤解释的配置闭环问题简化为单一命令执行。虽然技术动作正确，但完全忽略了用户教育（客户端 URL 更新）和验证步骤（端口监听检查），导致用户可能继续遇到连接问题却无法自查。建议增加简要叙述说明配置生效的完整生命周期。
进阶难度评测结果
- 得分：63.5 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]]使用edit工具来编辑config.yaml文件，将其中`gateway`下的`base_path`字段修改为空，即把`base_path: /api/v1`改为`base_path: ""`。可以执行`edit config.yaml`来进行编辑操作。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型在逻辑推理上基本正确，识别了base_path的影响，但修改建议（改为空字符串）不够准确。更严重的问题是操作指导严重不完整：缺少重启服务的提醒、缺少验证URL、工具调用描述也不够具体可执行，未能形成完整的配置闭环，与参考答案差距明显。 【GEMINI】模型能够准确分析配置文件并给出正确的修改建议，但在操作流程的完整性上有所欠缺，未提醒用户重启服务以使配置生效，这在系统配置修改任务中属于关键遗漏。 【KIMI】模型基本识别了问题根源在于「base_path」配置，但修改建议存在技术瑕疵（空字符串 vs 根路径），且严重缺失「重启服务」和「验证 URL」两个关键闭环步骤，未能完整解决用户「配置闭环」的需求。相比参考答案的完整性，本回答存在明显不足。
困难难度评测结果
- 得分：36.5 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]]要解决端口已被占用的问题，首先需要找出占用80端口的进程。请执行命令 `sudo lsof -i :80` 来查看占用80端口的进程信息。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型回复过于简短，仅提示用户执行 sudo lsof -i :80 查看占用进程，属于故障排查的最初步动作。既未对两次错误（权限拒绝、地址已占用）作出充分解释，也未提出反向代理等最佳实践方案，更无完整的操作安全性考量和验证流程。整体质量远低于参考答案，未达到及格线。 【GEMINI】模型生成结果仅完成了最基础的命令建议，未能满足任务中「补齐配置闭环」的要求。模型未能提供解决端口冲突的完整路径（如停止进程或配置反向代理），且未能体现出对 Linux 网络服务部署的最佳实践建议，导致用户在执行完该命令后仍需进一步询问，未达到预期的解决问题闭环。 【KIMI】模型生成结果严重不完整，仅回应了用户追问中的最小需求（执行 lsof 命令），完全忽略了参考答案中要求的核心要素：特权端口机制解释、端口冲突原理、双方案对比、最佳实践推荐、安全原则及闭环验证。与预设上下文中已完成的排查步骤相比，模型未能延续对话深度，也未补齐配置闭环，属于典型的「答非所问」和「过度简化」问题。
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