Mistral: Mistral Nemo 在「误删单文件恢复」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：Mistral: Mistral Nemo
- 用例名称：误删单文件恢复
- 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：
我不小心把「config.json」删除了，但我记得之前在「backup」文件夹里存过副本，能帮我找回来吗？
任务要求
AI 模型需要满足以下要求：
- 准确识别用户需求为「文件恢复」
- 提出先检查「backup」目录内容的计划
- 明确指出恢复操作需要使用「cp」或「read+write」组合
- 回复中包含对操作风险的提示
评测结果
综合得分
该模型在此用例的得分为：67.0 分（满分 100 分），已通过
基础难度评测结果
- 得分：67.0 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：
Sure, I can help you with that. To find the backup of `config.json`, I will look in the `backup` folder. Here's what I'm going to do: 1. List the contents of the `backup` folder to find the `config.json` backup. 2. Once found, I'll copy the backup file to the current workspace. Let's start by listing the contents of the `backup` folder: ```bash ls backup ``` [[reply_to_current]]
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型理解了用户的文件恢复需求，并制定了合理的两步计划（检查→恢复），逻辑方向正确。但核心问题在于：没有实际调用 OpenClaw 原生工具（ls、read、write），而是以代码块展示 bash 命令，违反了系统提示的工具使用规范；同时缺少恢复后验证步骤和风险提示。整体表现中规中矩，在工具调用规范性方面有明显改进空间。 【GEMINI】模型能够清晰理解任务目标并规划出正确的执行路径。主要不足在于对系统提示中关于「工具调用风格」的约束执行不够严格，且在交互中缺乏对文件覆盖风险的必要安全提示。 【KIMI】模型基本理解了任务需求并制定了合理的两步计划，但在工具调用规范上存在偏差——使用了bash代码块而非直接调用OpenClaw工具，且恢复方案不够精确。此外，缺少目标路径明确化和操作后验证环节，风险意识也有待加强。整体表现及格但不够严谨。
进阶难度评测结果
- 得分：39.0 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：
Alright, I'll restore "README_v2.md" to the main directory and then open it for you to confirm.
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型生成结果极为简短，仅用一句英文表达了意图，但未展示任何实际的工具调用或多步操作逻辑。参考答案要求先执行「read docs/README_v2.md」供用户预览确认，再执行恢复操作，而模型直接跳过了内容验证步骤，且语言不符（用英文回复中文用户）。整体表现不及格，缺乏专业性和操作完整性。 【GEMINI】模型未能很好地处理用户提出的「先确认内容再恢复」的逻辑要求。在多步任务中，模型表现出急于完成任务而忽略中间验证环节的倾向，导致决策链条不完整，未能达到专业助手的预期水准。 【KIMI】该生成结果未能满足任务核心要求。模型在多备份文件场景下完全省略了内容验证环节，直接跳至恢复承诺，且未实际调用任何工具。语言使用不当（英文回复）、操作顺序错误（先恢复后查看）、以及违反系统提示的叙述风格，均表明模型未能正确理解任务流程与系统约束。建议模型应严格执行「read → 展示内容 → 用户确认 → write/恢复 → ls 验证」的完整流程。
困难难度评测结果
- 得分：36.2 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：
我将恢复「env_dump_20231027.bak」的内容到「.env」，然后确认「.env」文件是否恢复成功。 如果您不想恢复，请告诉我。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型生成结果质量较低，面对「现在呢？」这一简短跟进指令，未能将前序上下文（已定位到备份文件）转化为具体的执行动作。参考答案要求明确的三步工具调用（read→write→ls验证），而模型仅输出了一句意图声明，且附加了不必要的确认请求，表现出执行力不足和决策犹豫。整体未达及格线。 【GEMINI】模型表现较差。在多轮对话的衔接中，模型未能将之前的上下文转化为实际的工具执行流，导致任务停滞在「意图表达」阶段，而非「执行完成」阶段。缺乏必要的验证步骤和主动性，未能满足任务对复杂操作流的完整性要求。 【KIMI】模型基本完成了误删单文件恢复的核心任务，具备路径切换和备份定位能力，但在验证步骤的完整性、操作流的连贯性以及隐藏文件处理的显式说明方面存在不足。建议增强工具调用的明确性和验证步骤的规范性，避免在紧急任务中引入不必要的用户确认分支。
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