StepFun: Step 3.5 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：StepFun: Step 3.5 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：— 分（满分 100 分），未通过
基础难度评测结果
- 得分：— 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：
我来帮您快速诊断和解决 OpenClaw Gateway 的启动问题。让我先检查当前状态： openclaw gateway status
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【KIMI】候选输出严重不完整，仅包含一个初始的工具调用（openclaw gateway status），尚未产生任何实质性的因果分析或修复方案。模型似乎将输出截断或未完成推理过程，导致无法评估其分析能力和方案质量。从现有输出看，完全未达到任务要求的基本门槛。
进阶难度评测结果
- 得分：12.8 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：
.
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出质量极差，仅输出了一个针对当前目录的ls工具调用，完全没有基于对话上下文进行任何故障分析或推理。既没有识别出「数据库恢复后401仍持续」这一关键线索，也没有直接读取config.yaml进行配置核查，更没有给出任何综合建议。与参考答案相比，候选输出几乎没有实质性价值。 【GEMINI】模型表现不佳。面对明确的故障排查请求，模型没有进行逻辑推理，也没有利用已知的配置文件信息进行诊断，而是执行了无关的「ls」命令，未能完成任务要求的故障关联分析与配置检查。 【KIMI】候选输出严重偏离任务要求。用户已明确数据库已重启但 401 错误持续，核心任务是识别 API Key 配置错误为主因，并使用「read」工具检查 config.yaml。但候选输出仅执行了无关的「ls」命令，既未完成故障关联分析，也未使用正确的工具获取配置信息，无法推进问题解决。
困难难度评测结果
- 得分：32.5 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：
cat /etc/openclaw/config.yaml
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出极为简陋，仅包含一个查看配置文件的工具调用，没有对已发生的两个错误进行任何分析、根因定位或修复建议。与参考答案相比，缺少备份操作、配置修复步骤、重启命令和健康验证等关键环节，整体质量远低于及格线，无法满足多重报错排查的任务要求。 【GEMINI】模型在技术诊断上表现出色，能够迅速定位到配置冲突的根源。但在任务执行层面，模型过于依赖工具调用，缺乏对用户进行必要的进度同步和后续步骤的明确规划。建议在执行具体操作前，先向用户简述修复方案，以体现对「数据安全性」的考虑（如备份）及恢复路径的完整性。 【KIMI】候选输出严重不合格。面对用户明确的「现在呢？」询问，以及对话上下文中已经清晰呈现的双重故障（权限问题已解决、配置不兼容待处理），候选输出仅执行了一个查看配置文件的命令，完全没有：1）分析当前状况；2）识别配置项弃用问题；3）提出备份和修复方案；4）给出验证步骤。这与参考答案中完整的四步恢复路径（备份→清理配置→重启→验证）形成鲜明对比，未能满足任务描述中「识别主因和次因，给出最短恢复路径」的核心要求。
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