Google: Gemma 4 26B A4B 在「批量重命名文件」的评测结果

基本信息

• 模型名称：Google: Gemma 4 26B A4B
• 用例名称：批量重命名文件
• 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：

请将「/workspace/docs」目录下所有以「temp_」开头的 .txt 文件重命名，去掉「temp_」前缀，并保持后缀不变。操作前请先列出文件确认。

任务要求

AI 模型需要满足以下要求：

1. 准确识别需要重命名的文件范围（temp_*.txt）
2. 提出先使用「ls」或「find」进行检查的计划
3. 给出正确的重命名逻辑（如使用 mv 或 rename 命令）
4. 强调操作的原子性或确认步骤以防误改

评测结果

综合得分

该模型在此用例的得分为：81.5 分（满分 100 分），已通过

基础难度评测结果

• 得分：81.5 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: "/workspace/docs"}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】模型能够理解任务核心要求，并严格遵守系统提示词中的“静默调用”规则（不进行多余叙述）。在执行逻辑上，成功识别了预检查的必要性，但在工具调用的参数构造上可以更加精确（如增加过滤条件）。 【KIMI】整体而言，该回答在逻辑严谨性方面表现较好，遵循了先检查再操作的原则，并提出了正确的重命名逻辑。但在工具调用准确性方面存在一些不足，'ls'命令调用不完整，缺少了通配符。如果能够修正这一问题，将进一步提高答案的准确性和完整性。

进阶难度评测结果

• 得分：93.0 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：

好的，我明白了。我会采用以下逻辑进行操作： 1. 遍历 `images` 目录下的所有 `.jpg` 文件。 2. 为每个文件计算新的目标名称 `photo_n.jpg`。 3. **检查冲突**：如果目标文件名已存在，则跳过该文件并记录冲突信息。 4. **执行重命名**：如果目标文件名不存在，则执行重命名。 我将先通过脚本来完成这个逻辑，以确保操作的原子性和准确性。 thought call:exec{command: "python3 -c \" import os directory = '/workspace/images' files = sorted([f for f in os.listdir(directory) if f.endswith('.jpg')]) skipped = [] renamed = [] for i, filename in enumerate(files, start=1): old_path = os.path.join(directory, filename) new_name = f'photo_{i}.jpg' new_path = os.path.join(directory, new_name) # 如果当前文件名已经是目标文件名，则无需操作（或者视为已完成） if filename == new_name: continue if os.path.exists(new_path): skipped.append(f'{filename} -> {new_name} (冲突: 文件已存在)') else: try: os.rename(old_path, new_path) renamed.append(f'{filename} -> {new_name}') except Exception as e: skipped.append(f'{filename} -> {new_name} (错误: {str(e)})') print('--- 重命名结果 ---') for r in renamed: print(f'[成功] {r}') if skipped: print('\\n--- 跳过/错误记录 ---') for s in skipped: print(f'[跳过] {s}') else: print('\\n没有冲突或错误发生。') \""}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】模型非常出色地完成了任务。相比于参考答案的简单 Shell 脚本，模型提供的 Python 脚本更加健壮，考虑到了文件已重命名、路径拼接以及异常处理等细节。模型严格遵循了用户提出的‘冲突时跳过并记录’的指令，逻辑闭环且日志清晰。 【KIMI】整体上，候选人的输出较好地满足了任务要求，特别是在冲突处理能力方面，通过检查目标文件路径的存在性来避免覆盖现有文件，并提供了详细的操作日志。在任务闭环度方面，虽然实现了文件遍历和序号递增，但对特殊情况的处理说明不够明确。

困难难度评测结果

• 得分：80.5 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：

目前的情况是：批量重命名任务**处于半完成状态**。 具体文件状态如下： * ✅ `access.log` $\rightarrow$ `backup_access.log` （**成功**） * ❌ `error.log` $\rightarrow$ `backup_error.log` （**失败**，权限不足） * ❌ `system.log` $\rightarrow$ `backup_system.log` （**未处理/失败**） **下一步建议：** 由于 `/var/log/app/` 目录权限受限，我需要使用 `sudo` 来执行重命名操作，或者如果你有权限，我可以尝试将这些文件复制到你的当前工作目录进行处理。 **你想让我尝试用 `sudo` 重新执行吗？** (这可能需要你输入密码或确认权限)

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】模型表现良好，能够精准诊断 shell 命令执行后的中间状态和权限问题。其优点在于状态总结非常直观（使用了 Emoji 和列表），易于用户理解。不足之处在于，针对“困难档”任务，其对“回滚策略”这一关键安全要求的响应不够充分，更倾向于“向前修复”而非“回滚恢复”，在处理生产环境敏感文件（如日志）时，缺乏对系统一致性的极致追求。 【KIMI】整体而言，候选人输出在处理异常和复杂环境决策方面表现良好，但在异常恢复能力上还有提升空间，特别是在明确提出回滚策略方面。

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：「批量重命名文件」
• 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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