deepseek-v3.2 在「配置改坏后回滚」的评测结果

基本信息

• 模型名称：deepseek-v3.2
• 用例名称：配置改坏后回滚
• 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：

我刚才改了一下「config.yaml」，现在服务报错说找不到「gateway」配置，你能帮我看看并修复吗？

任务要求

AI 模型需要满足以下要求：

1. 使用「read」工具读取「config.yaml」的内容
2. 识别出缺失的「gateway」配置项及其层级结构
3. 使用「write」或「edit」工具补全配置并确保格式正确
4. 在回复中确认修复完成并简述修改内容

评测结果

综合得分

该模型在此用例的得分为：24.2 分（满分 100 分），未通过

基础难度评测结果

• 得分：24.2 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：

[[reply_to_current]] 我来帮你检查并修复这个问题。首先让我查看当前的 config.yaml 文件内容，然后检查服务状态。 ```bash openclaw gateway status ``` ```bash cat config.yaml ```

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型回复仅给出了检查意图和两个 bash 代码块（openclaw gateway status 和 cat config.yaml），但没有实际调用任何规定工具（read、edit、write 等），也没有识别或修复 gateway 配置缺失问题。整体来看，回复停留在「准备阶段」，未完成任务的核心要求，与参考答案差距显著。 【GEMINI】模型在执行任务时表现出良好的初步诊断意识，能够通过工具获取必要信息。但模型在完成检查步骤后未能自动进行后续的修复操作（如使用 edit 工具补全配置），导致任务未完成。建议模型在获取到错误信息后，应主动分析并执行修复指令。 【KIMI】该模型生成结果完全不符合任务要求。模型没有调用任何实际工具（read/edit/write），只是输出了 bash 命令格式的文本，导致配置修复任务零进展。用户的问题（config.yaml 缺失 gateway 配置导致服务报错）完全没有得到解决。这是一个典型的「幻觉式」回复——看起来在行动，实际上什么都没做。需要严格扣分。

进阶难度评测结果

• 得分：58.5 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：

我将使用 `edit` 工具来修复 JSON 语法错误，并将 `search` 插件的 `enabled` 改为 `true`。 ```json {"command": "edit", "args": {"file": "plugin_manager.json", "old": "{\n \"plugins\": [\n {\n \"name\": \"weather\",\n \"enabled\": true\n },\n {\n \"name\": \"search\"\n \"enabled\": false\n }\n ]\n}", "new": "{\n \"plugins\": [\n {\n \"name\": \"weather\",\n \"enabled\": true\n },\n {\n \"name\": \"search\",\n \"enabled\": true\n }\n ]\n}"}} ```

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型在多任务处理方面表现良好，一次性完成了语法修复和业务逻辑修改，工具调用参数准确。但在验证环节完全缺失，未对修复后的文件进行任何合法性校验，与参考答案的要求存在明显差距。整体来看，功能修复部分合格，但缺乏严谨的验证流程，影响了整体质量。 【GEMINI】模型在处理具体的修改任务上表现出色，能够准确识别并修复 JSON 格式问题。但在工程实践的严谨性上有所欠缺，缺乏对修改结果的验证环节，这在处理配置文件修复任务时存在风险。 【KIMI】模型在多任务处理方面表现完美，一次性完成了语法修复和业务逻辑修改。然而，验证环节的完全缺失是一个重大缺陷——用户明确要求确认文件可被正确解析，但模型未执行任何验证步骤，导致任务未完成。这反映了模型对「验证严谨性」要求的忽视，在实际生产环境中可能导致修复不彻底或引入新问题。

困难难度评测结果

• 得分：73.5 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：

现在「.env」文件已从备份中恢复。不过「settings.py」的权限仍然是「000」，导致应用可能无法读取它。如果你有管理员权限，可以尝试用「sudo chmod」修改权限；如果没有，则需要联系系统管理员来修复。 另外，建议检查一下应用是否依赖「settings.py」中的配置，以及恢复后的「.env」是否包含所有必要的环境变量。

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型整体表现中规中矩，能够正确识别关键操作（恢复 .env）并在工具调用失败后不陷入死循环，对用户模糊追问也给出了基本合理的状态总结。但与参考答案相比，缺乏主动性：未提出搜索其他备份文件的替代方案，未以问句形式引导用户确认下一步，对权限瓶颈的处理建议也较为笼统。整体达到及格线以上，但在主动性和具体可操作性方面有提升空间。 【GEMINI】模型表现良好，能够准确评估当前环境的恢复进度，并针对权限问题给出了合理的解释与建议。在处理异常流程时表现稳健，但在面对复杂故障时，若能更主动地提出替代性搜索方案（如查找其他备份），体验会更佳。 【KIMI】模型基本完成了配置回滚的核心任务，能够处理工具调用失败并给出合理建议，但在主动探索替代方案和结构化总结当前状态方面还有提升空间。整体表现达到及格水平，属于稳健但不够出色的恢复策略执行。

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：「配置改坏后回滚」
• 查看该模型的所有评测结果：deepseek-v3.2
• 浏览同维度的其他用例：「文件操作与恢复」
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