Google: Gemma 4 26B A4B 在「误删单文件恢复」的评测结果

基本信息

• 模型名称：Google: Gemma 4 26B A4B
• 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：

1. 准确识别用户需求为「文件恢复」
2. 提出先检查「backup」目录内容的计划
3. 明确指出恢复操作需要使用「cp」或「read+write」组合
4. 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：63.5 分（满分 100 分），已通过

基础难度评测结果

• 得分：63.5 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：

call:ls{path: "."}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】模型表现较差。虽然工具调用格式正确，但完全忽视了用户提供的关键上下文信息（backup 文件夹），且在处理文件恢复这种敏感且多步骤的任务时，未按照系统提示词的要求进行必要的计划说明或风险提示，逻辑链条不完整。 【KIMI】模型基本理解了用户的需求，并提出了检查备份目录的计划。但在路径指定和工具使用方面存在一些不足，需要进一步优化。

进阶难度评测结果

• 得分：89.5 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：

call:read{file: "docs/README_v2.md"}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】模型在多文件备份场景下表现出色，能够准确识别目标文件并优先执行验证逻辑。其操作完全符合系统预设的工具调用规范，决策路径清晰且正确。 【KIMI】整体上，模型表现出了较好的多步决策能力和专业度，但在交互细节上还有提升空间。

困难难度评测结果

• 得分：88.0 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：

既然已经找到了备份文件 `/tmp/env_dump_20231027.bak`，我现在的任务是将其内容恢复到你误删的 `.env` 文件中。 我将执行以下步骤： 1. **读取**备份文件的内容。 2. **写入**到当前目录下的 `.env` 文件。 3. **验证**文件是否已成功恢复。 开始执行： thought call:exec{command: "cat /tmp/env_dump_20231027.bak > .env && ls -a .env"}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】模型在处理中断后的任务恢复方面表现出色，能够完美理解对话历史并补全操作。其恢复策略正确，执行效率高。但在工具选择上未完全遵循‘优先使用原生工具’的指引，且在验证环节对‘权限’的检查不够细致，未达到满分标准。整体而言，是一个非常可靠的助手表现。 【KIMI】模型在异常处理与恢复方面表现出色，能够灵活应对权限问题并成功定位备份文件。在复杂场景下，模型能够维持任务目标并执行复杂的操作流程。尽管在命令调用上存在一些语法错误，但整体上模型的表现是优秀的。

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：「误删单文件恢复」
• 查看该模型的所有评测结果：Google: Gemma 4 26B A4B
• 浏览同维度的其他用例：「文件操作与恢复」
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