OpenAI: GPT-5.4 在「考勤表格式创建」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：OpenAI: GPT-5.4
- 用例名称：考勤表格式创建
- 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：
请帮我创建一个班级考勤登记表的Excel文件（attendance.xlsx）。要求：第一列为学生姓名（预留10行），横向排列5个工作日（周一至周五），每天分为"上午"和"下午"两个子列，日期行与子列行之间使用合并单元格（即每个日期占两列并居中合并），整个表格添加全边框。
任务要求
AI 模型需要满足以下要求：
- 生成一个名为 attendance.xlsx 的Excel文件
- 第一列为"姓名"列，预留至少10行空行供填写
- 横向包含周一至周五共5个工作日
- 每个工作日下分为"上午"和"下午"两个子列
- 每个工作日标题单元格横向合并两列并居中显示
- 整个表格区域设置全边框（上下左右边框线）
评测结果
综合得分
该模型在此用例的得分为：32.0 分（满分 100 分），未通过
基础难度评测结果
- 得分：32.0 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：
我先在工作区里创建一个带格式的 `.xlsx` 文件。为确保真正生成 Excel 并包含合并单元格与边框，我会用脚本直接写出文件。 [[reply_to_current]]我会先检查环境里是否有可用的 Excel 生成库；如果没有，我会用兼容方式生成 `attendance.xlsx`。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【KIMI】整体来看，候选人对任务有基本的理解，提到了使用脚本创建Excel文件，但对合并单元格和全边框设置的细节描述不足。如果能提供更具体的实现细节，将更符合任务要求。 【GEMINI】模型未能执行用户指令，仅停留在口头描述计划和 narrate（叙述）阶段，违反了系统提示词中“不要叙述常规、低风险的工具调用”以及“直接使用工具”的原则。由于没有产生任何实际的输出结果（文件或代码），该生成结果未满足任务定义的任何功能性指标。
进阶难度评测结果
- 得分：4.0 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：
我将直接生成一个 .xlsx 文件并做一次程序化校验：合并区域、全边框、以及从 2025-01-06 起的 10 个工作日；同时把两行表头设为浅蓝色。先检查下工作区里是否已有相关文件，避免覆盖错文件。 [[reply_to_current]]
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【KIMI】该候选输出是一个典型的「幻觉式承诺」案例：模型用自信的语气声称将要完成多项任务（生成文件、校验合并区域、设置边框和背景色等），但实际上完全没有调用任何工具来执行这些操作。整个回复仅包含文字描述和意图表达，没有任何可验证的交付物。在功能评测场景下，这种输出属于严重的不完成任务，所有核心功能均未实现。模型似乎误解了「回复」与「执行」的区别，将计划描述当作了实际交付。 【GEMINI】模型在需求理解和逻辑规划上表现良好，准确捕捉到了用户关于日期、合并单元格和样式的细节要求。然而，作为 AI 助手，它在本次交互中仅提供了文字回复，未能在 OpenClaw 环境中发起任何实际的工具调用来创建文件，导致任务目标完全未达成。这种“有计划无执行”的行为使其生成结果在功能性上不合格。
困难难度评测结果
- 得分：34.5 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，我会按这 5 项要求更新 Excel 文件，并保留原有全边框设置。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】模型在面对具体且复杂的文件处理任务时，仅给出了简单的口头确认回复，完全没有履行其实际职能。在 OpenClaw 这种具备工具调用能力的系统环境下，模型应当直接调用 write 或 edit 等工具生成 Excel 文件，而该模型仅产生了一句确认语，导致所有功能性指标均未达成，属于严重的任务执行失败。 【KIMI】模型整体上较好地理解并追踪了用户的变更意图，并提到了会按照要求更新Excel文件。但在合并单元格、多层格式叠加以及冻结窗格与列宽设置的具体实现细节方面，模型的输出略显不足，没有提供足够的信息来完全验证其是否能够完全满足所有要求。因此，整体评分为中等偏上水平。
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