Google: Gemma 4 26B A4B 在「表格标题行加粗」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：Google: Gemma 4 26B A4B
  • 用例名称：表格标题行加粗
  • 测试类型：xsct-a
  • 评测维度：文档格式排版

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：

以下是当前工作区中的数据文件 `orders_q3.csv` 内容（前10行）： ```csv 客户ID,客户姓名,订单编号,下单日期,商品名称,数量,单价,总金额,状态 C001,赵建国,ORD-2024-0801,2024-08-01,办公椅,2,580,1160,已完成 C002,李梅,ORD-2024-0802,2024-08-02,打印机,1,2300,2300,已完成 C001,赵建国,ORD-2024-0803,2024-08-05,墨盒×10,3,45,135,已完成 C003,王鹏,ORD-2024-0804,2024-08-07,显示器,2,1800,3600,已完成 C002,李梅,ORD-2024-0805,2024-08-10,键盘,1,320,320,退款中 C004,张晓燕,ORD-2024-0806,2024-08-12,移动硬盘,2,450,900,已完成 C001,赵建国,ORD-2024-0807,2024-08-15,办公桌,1,1200,1200,已完成 C003,王鹏,ORD-2024-0808,2024-08-18,路由器,1,380,380,配送中 C005,陈伟,ORD-2024-0809,2024-08-20,笔记本支架,3,180,540,已完成 C002,李梅,ORD-2024-0810,2024-08-22,耳机,2,260,520,已完成 ``` （共 87 条记录） 请将上述CSV数据转换为Markdown格式的表格，写入文件 `orders_q3_formatted.md`。要求：表头行（即

任务要求

AI 模型需要满足以下要求：

  1. 输出文件为 orders_q3_formatted.md
  2. 表格为标准Markdown表格格式，包含表头行、分隔行和数据行
  3. 表头行中每个字段名使用Markdown加粗语法（即用 ** 包裹），如 **客户ID**
  4. 数据行内容与原CSV数据一致，不做任何加粗或其他样式修改
  5. 表格包含全部10行数据记录，列数为9列

评测结果

综合得分

该模型在此用例的得分为：38.7 分（满分 100 分），未通过

基础难度评测结果

  • 得分：38.7 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，我会将 `orders_q3.csv` 的数据转换为 Markdown 格式的表格，并保存到 `orders_q3_formatted.md` 中。 由于你提供的示例仅包含前 10 行，我将首先读取完整的 `orders_q3.csv` 文件，以确保转换的是全部 87 条记录。 首先，我检查一下文件是否存在并读取内容。 thought call:exec{command: "cat orders_q3.csv"}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】模型未能完成将 CSV 数据格式化并写入文件的核心任务。尽管模型在回复中准确复述了加粗表头的要求，并表现出作为 AI Agent 检查完整数据的逻辑，但它忽视了用户要求处理“上述”已提供数据的明确指令。由于它在第一步选择了读取文件而非直接生成并写入结果，导致最终没有任何实质性的格式化输出或文件写入动作，任务达成度极低。 【KIMI】模型在理解和计划执行任务方面表现良好，正确理解了Markdown格式要求，并计划完整地处理所有数据。虽然模型没有直接展示写入文件的步骤，但其计划和方法符合任务要求，因此整体表现优秀。

进阶难度评测结果

  • 得分：1.0 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:edit{edits: [[1, 1, 1, 0, "## 活动主题"], [13, 13, 13, 0, "## 核心目标"], [21, 21, 21, 0, "## 物质准备"], [26, 26, 26, 0, "## 活动流程"], [31, 31, 31, 0, "## 教师支持策略"]]]}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】模型表现极差，未能完成任何核心任务。用户要求保留加粗格式并改写正文主题为“迷宫构建”，而模型却通过工具调用删除了标题的加粗和编号，且完全忽略了正文改写的要求。此外，模型仅提供了极简且错误的 edit 指令，未按要求输出修改后的完整内容。 【KIMI】模型的输出完全不符合任务要求，既没有保留原有的Markdown格式，也没有对文件内容进行任何修改，更没有体现出对用户指令的遵循。

困难难度评测结果

  • 得分：52.8 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:edit{edit: "Replace the title from '第三季度办公用品采购分析报告' to '第三季度跨部门IT资产调拨与租赁综合分析报告'. Update the table in section '二、数据来源' with the new data, ensure the format matches, and add the italicized note '注：以上为调拨与租赁混合台账，单价单位为元/月。' below it. Recalculate and update the '四、订单状态分布' table based on the new data (租赁中: 2, 已归还: 2, 逾期未还: 1). Keep all other bold formatting unchanged.",file: "quarterly_report.md"}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】模型的表现非常差。它没有执行具体的文档编辑和内容生成任务，而是试图通过一个包含自然语言描述的工具调用来“命令”系统完成工作。它忽略了将结果写入新文件（final_report.md）的关键指令，且未提供任何实际重写后的文本内容（如客户频次分析、总结建议、百分比计算等）。除了捕获到标题的变更外，几乎没有完成任何实质性的功能要求。 【KIMI】整体而言，候选人较好地理解并执行了用户的指令，特别是在格式保留和意图变更追踪方面做得较好。但在内容替换与计算准确性以及工具调用合理性方面存在一定的不足，特别是对于状态统计和最终文档写入的明确性。

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