StepFun: Step 3.5 Flash 在「onboard 权限报错」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：onboard 权限报错
- 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：
我在执行「openclaw onboard」时，终端提示「EACCES: permission denied, mkdir '/usr/local/lib/openclaw'」，我该怎么办？
任务要求
AI 模型需要满足以下要求：
- 准确识别报错原因为「目录写入权限不足」
- 提供使用「sudo」提升权限的解决方案
- 建议检查当前用户对目标路径的「所有权」
- 说明 onboard 命令在初始化过程中的作用
评测结果
综合得分
该模型在此用例的得分为：23.8 分（满分 100 分），未通过
基础难度评测结果
- 得分：23.8 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：
我来帮您解决这个权限问题。让我先检查一下当前的环境和 openclaw 命令的情况。 whoami && id
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出几乎没有任何实质性内容。模型仅表示「我来帮您解决」并调用了一个查询当前用户信息的工具调用，就结束了输出。既没有对 EACCES 错误原因做出任何诊断，也没有给出任何修复方案。与参考答案相比，参考答案清晰解释了错误原因（/usr/local/lib 目录写入权限不足）、提供了两种修复方案（sudo 运行或 chown 更改所有权），而候选输出完全是空洞的。这是一个严重不完整的回答，对用户毫无帮助。 【GEMINI】模型在接收到任务后，采取了通过工具调用进行诊断的策略，这符合「OpenClaw」的操作规范。然而，在面对明确的「EACCES」权限报错时，模型未能直接给出诊断结论或解决方案，而是停留在检查当前用户身份的初步阶段，导致任务完成度较低，未能满足用户快速解决问题的需求。 【KIMI】候选输出表现不佳。用户已经明确给出了完整的错误信息，但模型没有直接回应问题，而是选择执行一个不必要的诊断命令（whoami && id）。这种「过度诊断」行为在错误原因已经显而易见的情况下是低效的。模型完全没有：1）解释 EACCES 错误的含义；2）说明 onboard 命令的作用；3）提供任何修复方案。相比之下，参考答案直接、精准地定位了权限问题，并给出了两种符合安全实践的解决方案。候选输出需要大幅改进，应在用户已提供明确错误信息时直接给出解决方案，而非进行冗余的环境检查。
进阶难度评测结果
- 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：
系统报错（阶段=模型生成; 模块=app.services.inference.call_text_model; provider=openrouter; model=stepfun/step-3.5-flash）：[app.services.inference.call_text_model][provider=openrouter][model=stepfun/step-3.5-flash] HTTP 405
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】由于模型在生成过程中触发了 HTTP 405 错误，未能输出任何实质性的诊断建议或解决方案，导致评测任务完全失败。模型未能履行作为助手的功能，无法满足任何评分维度的要求。 【KIMI】候选输出为系统错误信息（HTTP 405），表明模型调用失败，未生成任何有效回复内容。无法完成评测任务中要求的权限问题诊断、修复方案提供及后续引导。这是一个完全失败的生成结果，所有评分维度均为 0 分。 【CLAUDE】候选输出为模型推理服务调用失败产生的系统错误信息（HTTP 405），并非对用户问题的实际回答。模型完全未能处理「openclaw onboard」权限报错的诊断与修复任务，既无逻辑推导，也无任何可操作的方案内容，两个维度均为0分。
困难难度评测结果
- 得分：74.5 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：
让我检查配置文件和 Gateway 状态，了解接下来可用的功能。 ~/.openclaw/config.yaml openclaw gateway status
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】模型展现了良好的工具使用和状态验证能力，但在解决权限受限后的“后续操作指导”上表现不足。它倾向于进行内部检查而非向用户提供明确的下一步操作建议（如设置环境变量和启动 Gateway），在知识点的覆盖上不够全面。 【KIMI】整体来看，模型在遇到权限问题时能够灵活应对，主动寻找替代方案，显示出较强的复杂问题解决能力。同时对 OpenClaw 的配置加载机制也有一定的了解。但在环境变量的解释上还有提升空间，需要更全面地掌握 OpenClaw 的配置机制。
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