doubao-seed-1-6 在「整理下载目录」的评测结果

基本信息

• 模型名称：doubao-seed-1-6
• 用例名称：整理下载目录
• 测试类型：xsct-a
• 评测维度：文件操作与恢复

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：

帮我收拾一下下载目录，里面乱糟糟的。

任务要求

AI 模型需要满足以下要求：

1. 主动调用「ls」工具查看当前目录下的文件列表
2. 根据文件后缀名提出合理的归类计划（如：图片、文档、安装包）
3. 在执行任何移动操作前，先向用户确认分类逻辑

评测结果

综合得分

该模型在此用例的得分为：35.2 分（满分 100 分），未通过

基础难度评测结果

• 得分：35.2 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：

[{"name":"ls","parameters":{"path":"~/Downloads"}}]

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型仅输出了一个「ls」工具调用，迈出了正确的第一步，但整个响应就此截止，缺少对目录内容的分析、归类方案的提出以及向用户确认的关键环节。与参考答案相比，模型只完成了约20%的任务要求，整体表现不及格。 【GEMINI】模型在执行第一步操作（查看目录）时表现正确，但未能根据任务要求进行后续的分析与交互。模型在调用工具后直接结束了回复，导致任务中断，未能体现出作为个人助理的规划与沟通能力。 【KIMI】模型生成结果严重不完整。用户要求「收拾一下」下载目录，模型仅执行了「ls」工具调用查看目录内容，但随后没有返回任何结果、没有提出归类方案、没有向用户确认执行意向，任务处于中断状态。这不符合任务要求的「先查看文件类型和结构，再执行归类或重命名」的完整流程，尤其缺乏「向用户确认」这一关键环节。与参考答案相比，差距显著。

进阶难度评测结果

• 得分：59.8 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：

exec {"command": "mkdir 旧版备份 && mv report_v1.pdf 旧版备份/"}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型在指令执行层面基本正确，工具调用命令符合用户要求（创建「旧版备份」目录并移动 report_v1.pdf）。但输出仅有工具调用而无任何文字反馈，未向用户确认操作结果，也未说明 report_final.pdf 等文件的处理情况，交互闭环性严重缺失。一个完整的回复应在工具调用后附上操作完成的确认说明。 【GEMINI】模型在执行任务的技术层面表现准确，能够正确使用 shell 命令完成文件操作。但在交互体验上存在明显缺失，未能根据任务完成情况向用户进行反馈，导致用户无法确认任务是否已成功执行。 【KIMI】该候选输出在执行层面完全正确，准确完成了创建「旧版备份」目录并移动「report_v1.pdf」的核心任务。然而，它犯了一个关键错误：完全没有向用户提供任何反馈或确认信息。在多轮对话的上下文中，用户期待的是操作完成后的闭环确认，而非静默执行。参考答案明确展示了应有的交互方式——告知用户操作已完成并说明文件状态。候选输出的工具调用虽然正确，但缺乏必要的用户沟通，导致交互闭环性严重不足。

困难难度评测结果

• 得分：86.7 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：

exec {"command": "sudo mkdir -p /var/backups/downloads_temp/ && sudo mv /var/downloads/temp/*.conf /var/backups/downloads_temp/ && sudo mv /var/downloads/temp/*.txt /var/backups/downloads_temp/ && sudo rm /var/downloads/temp/*.bin"}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】模型表现优秀，能够精准捕捉用户在上下文中的隐含意图。在技术实现上，它完美处理了 sudo 权限提升和文件分类逻辑（备份 vs 删除）。其操作流程符合专业运维直觉，使用了 mkdir -p 并创建了合理的备份路径。唯一的小缺憾是缺乏操作后的状态确认步骤（如 ls），且没有附带任务要求的操作清单说明。 【KIMI】整体而言，模型在权限异常恢复、操作安全性和复杂任务决策方面表现良好，能够根据文件类型采取差异化处理。但在删除文件前缺乏用户确认，且对边界情况的处理不够完善。建议在删除文件前增加用户确认环节，并在处理过程中增加对边界情况的预判和处理。

相关链接

您可以通过以下链接查看更多相关内容：

• 查看所有模型在此用例的表现：「整理下载目录」
• 查看该模型的所有评测结果：doubao-seed-1-6
• 浏览同维度的其他用例：「文件操作与恢复」
• 返回排行榜首页