StepFun: Step 3.5 Flash 在「安装成功但服务未启动」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：StepFun: Step 3.5 Flash
- 用例名称：安装成功但服务未启动
- 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：
我刚才运行了安装命令，显示「Installation Success」，但是我现在访问 http://localhost:8000 没反应，我该怎么确认服务到底起没起来？
任务要求
AI 模型需要满足以下要求：
- 准确指出应使用「ps」或「systemctl」检查进程状态
- 提示检查 Gateway 默认端口 8000 的占用情况
- 建议查看「logs」目录下的日志文件进行故障定位
- 回复内容需包含具体的验证命令示例
评测结果
综合得分
该模型在此用例的得分为：64.0 分（满分 100 分），已通过
基础难度评测结果
- 得分：64.0 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：
我来帮你检查服务状态。首先看看端口8000是否有进程在监听： ss -tlnp | grep :8000 || netstat -tlnp 2>/dev/null | grep :8000 || lsof -i :8000 2>/dev/null
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选回复仅执行了端口监听检查这一步，虽然命令本身正确且有一定专业性，但遗漏了进程检查（ps）和日志查看两个关键排查步骤，也未提及如何手动启动服务，整体排查路径不完整。对比参考答案三步骤的系统性指导，此回复在覆盖度上差距明显，属于「部分正确但不完整」的回复。 【GEMINI】候选模型能够快速响应并执行有效的端口排查命令，体现了良好的工具使用能力。但作为 AI 助手，在处理「安装后服务未启动」的问题时，应优先使用项目内置的 CLI 工具（如「openclaw gateway status」）而非仅依赖通用 Linux 命令，同时应补充日志排查建议，以便用户更全面地定位问题。 【KIMI】候选输出仅完成了端口检查这一单一排查步骤，遗漏了进程状态检查、日志分析和手动恢复服务等关键内容，未能充分利用 System Prompt 提供的专用命令（如「openclaw gateway status」），排查逻辑不够全面。表达上虽直接执行工具调用，但缺乏完整的排查思路和后续指导，整体表现略低于及格线。
进阶难度评测结果
- 得分：52.2 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：
我来用更全面的方式检查一下端口占用情况，包括查看进程 1234 的状态。 sudo netstat -tlnp 2>/dev/null | grep :8000 || lsof -i :8000 ps -p 1234 -o pid,cmd
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出展示了合理的排查思路，通过 sudo 提权和 lsof 补充检查来应对 netstat 未显示结果的问题，工具调用本身无误。但核心不足在于：未向用户解释矛盾原因、未给出终止进程或修改端口的具体方案、未引导查阅和修改 config.yaml。整体停留在「继续诊断」而非「给出解决方案」的层面，与参考答案差距明显。 【GEMINI】模型在面对用户提出的矛盾点时，未能给出合理的解释或直接的解决方案，而是陷入了重复的排查循环。模型忽略了系统提示中关于 OpenClaw CLI 的使用建议，且未针对日志中明确的端口占用问题提供修改配置或强制释放端口的建议，导致用户问题未能得到实质性进展。 【KIMI】候选输出未能有效回应用户的核心困惑（日志与 netstat 结果矛盾），也未提供任何实质性的解决方案。工具使用存在格式问题和权限假设问题，且动作冗余、未指向问题解决。整体表现低于及格线，未能满足用户「服务启动不了，需要排查和恢复」的实际需求。
困难难度评测结果
- 得分：62.0 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：
服务已成功启动，PID 为 5678。需要我验证服务运行状态或查看日志吗？
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】该模型的表现较为消极。虽然它正确识别了服务已启动的状态，但其回复仅停留在复述上一条指令的表面结果上。在需要“手动恢复”和“排查”的复杂任务中，模型未能主动执行验证动作（如检查端口、健康检查、查看 Token），而是采取了“询问式”的被动交互方式，这大大降低了解决问题的效率，未能满足高难度任务的预期。 【KIMI】Assistant 在权限问题出现时采取了合理的绕过策略，但在服务启动后的验证不够全面，没有提供服务运行状态的详细信息。对于用户的简短追问，Assistant 给出了直接的响应，但回答不够完整。
相关链接
您可以通过以下链接查看更多相关内容：
