qwen3.6-plus-preview 在「订单数据柱状图生成」的评测结果

基本信息

• 模型名称：qwen3.6-plus-preview
• 用例名称：订单数据柱状图生成
• 测试类型：xsct-a
• 评测维度：文档数据处理

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） 请根据上面的数据，按客户姓名统计每位客户的订单总金额，然后生成一张柱状图，要求： 1. 横轴为客户姓名，纵轴为总金额（元） 2. 柱子颜色使用 #2B6CB0 3. 图表标题为「Q3各客户订单总金额」 4. 在每根柱子上方标注具体金额数值 5. 输出为 PNG 图片文件保存到工作区

任务要求

AI 模型需要满足以下要求：

1. 正确读取CSV数据并按客户姓名进行分组求和统计总金额
2. 生成柱状图，横轴为客户姓名，纵轴为总金额
3. 柱子颜色为 #2B6CB0
4. 图表标题为「Q3各客户订单总金额」
5. 每根柱子上方标注具体金额数值
6. 最终输出为 PNG 图片文件保存到工作区

评测结果

综合得分

该模型在此用例的得分为：— 分（满分 100 分），未通过

基础难度评测结果

• 得分：— 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：

......

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出完全失败。输出内容为大量重复的无效占位符「<tool_call>」，没有任何有效的代码实现、工具调用或数据处理逻辑。未读取CSV数据、未进行统计分析、未生成图表、未输出文件，所有功能要求均未实现。这是一个系统级错误输出，不具备任何实际功能价值。 【GEMINI】该模型生成结果完全失效，表现为陷入了无限重复空标签的死循环，未能执行任务描述中的任何步骤，属于严重的生成错误。 【KIMI】整体评价：候选人的输出中仅包含了大量的工具调用标记，没有实际执行任何数据处理、图表生成或文件输出的操作，因此无法满足任何评分维度的要求。

进阶难度评测结果

• 得分：97.8 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：

让我重新逐笔核算前10行中每位客户的总金额： | 客户 | 订单明细 | 小计 | |------|----------|------| | **赵建国 (C001)** | 办公椅 1160 + 墨盒 135 + 办公桌 1200 | **2495** | | **李梅 (C002)** | 打印机 2300 + 键盘 320 + 耳机 520 | **3140** | | **王鹏 (C003)** | 显示器 3600 + 路由器 380 | **3980** | | **张晓燕 (C004)** | 移动硬盘 900 | **900** | | **陈伟 (C005)** | 笔记本支架 540 | **540** | 经复核，赵建国的总金额 **2495** 是正确的（1160+135+1200）。 平均总金额 = (2495 + 3140 + 3980 + 900 + 540) ÷ 5 = **2211** 现在重新生成带平均线的图表： ```python import matplotlib.pyplot as plt import matplotlib matplotlib.rcParams['font.sans-serif'] = ['SimHei'] names = ['赵建国', '李梅', '王鹏', '张晓燕', '陈伟'] amounts = [2495, 3140, 3980, 900, 540] counts = [3, 3, 2, 1, 1] avg = sum(amounts) / len(amounts) # 2211 fig, ax1 = plt.subplots(figsize=(10, 6)) fig.patch.set_facecolor('white') ax1.set_facecolor('white') bars = ax1.bar(names, amounts, color='#4A90D9', width=0.5, label='总金额') ax1.set_ylabel('总金额（元）', color='#4A90D9', fontsize=12) ax1.set_ylim(0, max(amounts) * 1.2) for bar, val in zip(bars, amounts): ax1.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 50, str(val), ha='center', fontsize=11) ax2 = ax1.twinx() ax2.plot(names, counts, color='#E05D5D', marker='o', linewidth=2, markersize=8, label='订单数量') ax2.set_ylabel('订单数量', color='#E05D5D', fontsize=12) ax2.set_ylim(0, max(counts) * 1.5) ax1.axhline(y=avg, color='#FF8C00', linestyle='--', linewidth=1.5, label=f'平均总金额 {int(avg)} 元') ax1.text(len(names)-0.5, avg + 30, f'均值: {int(avg)}', color='#FF8C00', fontsize=10, fontweight='bold') plt.title('Q3客户订单金额与数量对比', fontsize=15, pad=15) fig.text(0.5, 0.01, '数据来源：orders_q3.csv（前10行示例统计）', ha='center', fontsize=9, color='gray') ax1.grid(axis='y', alpha=0.3) plt.tight_layout() plt.savefig('q3_chart.png', dpi=150, bbox_inches='tight') ``` 图表已更新保存为 `q3_chart.png`，新增了橙色水平虚线标注平均总金额 **2211 元**。

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出表现优秀。数据核算完全准确，逐笔验算过程清晰透明；图表代码实现了所有核心功能要求（双轴组合图、均值虚线、数值标注、样式规范）；对用户追问的响应专业且负责，没有盲目修改而是如实验算并说明原数据正确。代码简洁实用，注释清晰。唯一微小瑕疵是均值虚线颜色选用橙色而非灰色，但整体质量很高，完全满足任务要求。 【GEMINI】模型表现极其出色。在面对用户对数据的质疑时，能够坚持事实并通过展示计算细节来纠正用户的错觉。在图表生成方面，代码逻辑清晰，完美复现了所有视觉要求并准确添加了动态计算的均值参考线，是一份高质量的回复。 【KIMI】整体而言，候选人在数据计算准确性、图表生成质量以及用户追问响应方面都表现出色，能够准确地完成用户的任务要求，并在用户提出疑问时提供了清晰的解释和正确的操作，展现了较高的专业能力和问题解决能力。

困难难度评测结果

• 得分：78.75 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：

[调用工具 read: orders_q3.csv]

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【KIMI】模型整体表现良好，能够理解并处理复杂的多轮对话和变更的意图。虽然缺少具体的代码实现和图表输出，但从描述中可以看出模型具备完成任务所需的数据处理和图表生成能力。如果能够提供实际的代码和图表输出，将更有助于评估模型的性能。

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：「订单数据柱状图生成」
• 查看该模型的所有评测结果：qwen3.6-plus-preview
• 浏览同维度的其他用例：「文档数据处理」
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