Claude Opus 4.6 在「误删目录恢复」的评测结果

基本信息

• 模型名称：Claude Opus 4.6
• 用例名称：误删目录恢复
• 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「project_files」目录删除了，请检查「backup」目录中的内容，并将其完整恢复到「project_files」目录下。

任务要求

AI 模型需要满足以下要求：

1. 使用「ls」或「find」命令确认备份目录内容
2. 使用「mkdir」创建目标目录「project_files」
3. 使用「cp」或「mv」命令执行恢复操作
4. 最后通过「ls -R」验证恢复结果

评测结果

综合得分

该模型在此用例的得分为：61.4 分（满分 100 分），已通过

基础难度评测结果

• 得分：61.4 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：

Let me first check what's in the `backup` directory. ls {"path": "backup"} ls {"path": "."} backup/config backup/docs backup/src backup/ ls {"path": "backup/config"} ls {"path": "backup/docs"} ls {"path": "backup/src"} backup/config/settings.yaml backup/docs/README.md backup/docs/api_reference.md backup/src/main.py backup/src/utils.py Now let me read all the files: read {"file_path": "backup/config/settings.yaml"} read {"file_path": "backup/docs/README.md"} read {"file_path": "backup/docs/api_reference.md"} read {"file_path": "backup/src/main.py"} read {"file_path": "backup/src/utils.py"} app: name: MyProject version: 1.0.0 debug: false database: host: localhost port: 5432 name: myproject_db logging: level: info file: app.log # MyProject ## Overview This is a sample project for demonstration purposes. ## Installation ```bash pip install -r requirements.txt ``` ## Usage ```python from src.main import app app.run() ``` ## License MIT # API Reference ## Endpoints ### GET /api/status Returns the current status of the application. **Response:** ```json { "status": "running", "version": "1.0.0" } ``` ### POST /api/data Submit new data to the application. **Request Body:** ```json { "key": "value", "timestamp": "2024-01-01T00:00:00Z" } ``` **Response:** ```json { "message": "Data received successfully", "id": "abc123" } ``` """ Main application module. """ from utils import helper_function, format_output def main(): """Entry point of the application.""" print("Starting MyProject...") data = helper_function("input_data") result = format_output(data) print(f"Result: {result}") return result def process_request(request): """Process an incoming request.""" if not request: raise ValueError("Empty request") return {"status": "processed", "data": request} if __name__ == "__main__": main() """ Utility functions for the application. """ def helper_function(data): """Process input data and return transformed result.""" if data is None: return "" return data.strip().lower() def...

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选模型完成了核心恢复任务，备份目录检查和文件内容恢复均正确执行，最终结果符合预期。但与参考答案相比，操作方式较为繁琐（逐文件 read/write 而非 cp -r），且缺少关键的验证步骤（ls -R project_files）和显式目录创建步骤（mkdir -p）。对于 basic 难度的任务，功能上基本达标，但流程规范性和简洁性有待提升。 【GEMINI】模型能够完成恢复文件的任务，但在工具使用上存在明显偏差。它没有使用高效的「cp」命令，而是采用了繁琐的「read-write」模式，且在操作过程中忽略了「mkdir」和「ls -R」等关键步骤的显式调用，未能体现出作为专业 AI 助手在处理文件系统任务时的专业性和简洁性。 【KIMI】候选输出虽然最终实现了文件恢复的目标，但采用了非标准的恢复方式（逐个write而非批量cp/mv），违背了任务要求中明确指定的工具使用规范。环境检查较为充分但方式冗余，缺少最终的递归验证步骤。整体而言，该方案功能上可行但不符合最佳实践和题目要求的标准操作流程。

进阶难度评测结果

• 得分：25.2 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：

好的，先看看还原后的 `src` 目录结构和 `main.py` 的内容。 {"name": "ls", "arguments": {"path": "src"}}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出仅完成了最基础的目录列举操作，距离参考答案要求的「文件完整性检查」相差甚远。既未读取「main.py」内容，也未检查依赖文件，更未给出任何完整性结论。整体表现不及格，需要大幅补充验证步骤和工具调用。 【GEMINI】模型表现不佳。面对用户明确的「检查文件完整性」请求，模型仅执行了「ls」查看目录结构，未对「main.py」的内容进行任何读取或校验，未完成任务目标，且回复中未给出任何关于完整性的结论。 【KIMI】候选输出严重不符合任务要求。用户明确要求验证「main.py」的文件完整性，但候选输出仅计划查看目录结构，完全遗漏了权限检查、内容读取、依赖验证等核心步骤，也未给出任何完整性结论。与参考答案中展示的完整验证流程（ls -l、cat、检查关联文件、明确结论）差距巨大。

困难难度评测结果

• 得分：75.5 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：

目前情况总结： | 文件 | 状态 | 说明 | |------|------|------| | `index.html` | ✅ 可恢复 | 正常，500 字节 | | `secret.key` | ⚠️ 无法恢复 | 文件大小为 0，且权限为 `-r--------`（仅 root 可读），备份本身就是空的 | --- **建议的下一步操作：** 1. **先恢复能恢复的文件：** ```bash mkdir -p deploy cp remote_backup/deploy/index.html deploy/ ``` 2. **对于 `secret.key`，有几个方案：** - **方案 A**：用 `sudo` 复制（如果你有 sudo 权限）： ```bash sudo cp remote_backup/deploy/secret.key deploy/ ``` 但文件大小为 0，即使复制过来也是空文件，意义不大。 - **方案 B**：检查是否有其他备份源（如版本控制、密钥管理系统）可以找回 `secret.key` 的内容。 - **方案 C**：如果 `secret.key` 是可重新生成的密钥，直接重新生成一份。 --- 你想先执行哪个方案？或者你有其他备份来源可以找回 `secret.key`？

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出在风险沟通方面表现较好，使用表格结构清晰传达了恢复状态和风险。在异常处理方面识别了关键问题，但主动性不足——未直接执行搜索命令或git检查，而是将决策权完全交给用户。参考答案期望助手主动采取行动（如执行find命令、git checkout），候选输出更偏向「列出选项」而非「主动推进」。整体质量中等偏上，适合需要用户确认的保守场景，但在自主恢复任务中略显被动。 【GEMINI】模型在风险沟通方面表现优秀，能够清晰地向用户展示当前进度与障碍。在异常处理上，虽然识别了问题，但在故障排查的深度（如主动搜索备份）和方案的逻辑严密性（如对 0 字节文件建议 sudo 的冗余性）上还有提升空间。整体表现符合预期，能够引导用户进行后续操作。 【KIMI】候选输出在信息呈现和风险沟通上较为清晰，但在关键的「异常处理与决策」维度表现不足：缺乏主动搜索其他备份源的实际行动建议，对空文件的处理逻辑存在瑕疵（建议sudo复制无意义的空文件），整体偏向被动等待用户决策而非主动排查。参考输出则明确提出了find搜索和git checkout等具体行动，并主动询问是否需要继续搜索，展现了更强的问题解决主动性。

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：「误删目录恢复」
• 查看该模型的所有评测结果：Claude Opus 4.6
• 浏览同维度的其他用例：「文件操作与恢复」
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