Google: Gemma 4 26B A4B 在「只改一个字段」的评测结果

基本信息

• 模型名称：Google: Gemma 4 26B A4B
• 用例名称：只改一个字段
• 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：

请帮我更新一下主配置文件的版本号到「1.1.0」。

任务要求

AI 模型需要满足以下要求：

1. 准确识别目标文件为「config.json」而非备份文件
2. 使用「read」工具确认文件内容后再进行修改
3. 使用「edit」或「write」工具仅修改「version」字段

评测结果

综合得分

该模型在此用例的得分为：35.0 分（满分 100 分），未通过

基础难度评测结果

• 得分：35.0 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：

call:ls{path: "."}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出未能完成任务的任何核心步骤。面对「更新主配置文件版本号」这一明确需求，模型仅执行了目录列表操作就停止了，既没有定位「config.json」文件，也没有读取内容或执行修改。这表明模型在理解任务意图和规划操作流程方面存在严重不足，完全未达到基本功能要求。 【GEMINI】模型展现了极佳的逻辑严密性。面对存在同名字段干扰的复杂任务，它没有直接进行修改，而是严格按照“定位-确认-修改”的科学流程，从列出目录开始。这种处理方式比参考答案中直接读取特定文件更符合“定位”这一前置指令的要求。 【KIMI】模型没有正确理解任务要求，错误地调用了'ls'工具，而没有按照指示使用'read'和'edit'工具对'config.json'文件进行操作。

进阶难度评测结果

• 得分：61.0 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：

call:edit{path: "/app/core/manifest.json",text: "{\"name\": \"core\", \"status\": \"active\"}"}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出在路径识别方面表现完美，准确定位到核心模块配置文件。但在流程完整性方面存在严重缺陷，缺少必要的验证步骤，未能形成完整的操作闭环。用户明确要求「确认结果」，但候选输出没有执行任何验证操作，这是关键性缺失。 【GEMINI】模型在文件定位的准确性上表现优秀，但在任务执行的完整性上存在显著缺陷。它未能建立起‘检查-执行-验证’的闭环流程，尤其是忽略了用户和评测标准中强调的后期验证步骤，导致任务完成质量大打折扣。 【KIMI】模型在路径识别与隔离方面表现出色，但在流程完整性方面存在不足。虽然正确识别了核心模块的配置文件路径，但在执行修改后没有进行结果验证，导致无法确保修改成功。建议在修改后增加结果验证步骤，以提高流程的完整性。

困难难度评测结果

• 得分：76.2 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：

文件已修改成功。`/home/user/conf.yaml` 中的 `port` 字段已从 `80` 更新为 `8080`。 当前文件内容为： ```yaml server: port: 8080 timeout: 30 ```

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出在回答「现在呢？」时仅简单总结了修改结果，缺少对权限错误的回顾说明、对系统级配置未修改状态的提示，以及通过工具调用进行实际验证的步骤。与参考答案相比，结构化程度和完整性均有不足，但操作本身安全合规。 【GEMINI】模型在处理多文件同名字段冲突时表现出色，能够根据系统反馈（权限拒绝）灵活切换目标文件。在总结阶段，模型提供了结构化的反馈，清晰地告知了用户当前的系统状态和修改结果，完全满足任务要求。 【KIMI】模型整体表现良好，在异常处理、验证总结和操作安全性方面都展现出了较高的能力。在遇到权限错误时能够合理解释并主动切换策略，修改后能够主动验证结果，并在用户追问时提供了当前状态的总结。但在验证部分还有提升空间，如能展示修改前后内容对比，将使结果更加完整。

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：「只改一个字段」
• 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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