qwen3.6-plus-preview 在「客户订单统计分析」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：qwen3.6-plus-preview
- 用例名称：客户订单统计分析
- 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 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） 请帮我统计每位客户的订单数量和总消费金额，并按总消费金额从高到低排序，最后以表格形式呈现结果。
任务要求
AI 模型需要满足以下要求：
- 按客户ID或客户姓名进行分组统计
- 统计每位客户的订单数量（行数）
- 统计每位客户的总消费金额（总金额列求和）
- 按总消费金额从高到低排序
- 以清晰的表格形式呈现最终结果
评测结果
综合得分
该模型在此用例的得分为：20.9 分（满分 100 分），未通过
基础难度评测结果
- 得分：20.9 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：
Let me first read the complete file to get all 87 records. path orders_q3.csv
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出仅完成了任务的第一步（读取文件），未进行分组统计、金额汇总、排序或结果呈现等核心操作。这是一个未完成的响应片段，不具备评测所需的完整功能实现。 【KIMI】模型已经正确理解了任务要求，并开始执行读取文件的操作，这是进行准确统计的第一步。但是，由于模型尚未完成所有计算步骤和结果呈现，因此无法给出完整的结果呈现质量评分。整体来看，模型在数据理解和执行任务的初步步骤上表现良好，但在完成整个任务和呈现结果方面还有待完成。
进阶难度评测结果
- 得分：0.2 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：
[read] [read]
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出几乎为空，仅包含两个 [read] 工具调用标签和一个 </think> 标签，没有完成用户要求的任何分析任务。既没有统计计算结果，也没有异常检测，更没有Python可视化代码和数据洞察。这是一个完全失败的回答，未能满足任何评测要求。 【GEMINI】在本次评测中，模型表现极差。面对用户明确的统计分析、异常检测和可视化代码生成需求，模型仅输出了重复的工具调用标记 `[read]`，没有任何实质性的分析内容或代码产出。这表明模型未能理解任务的最终目标或在执行过程中出现了严重的逻辑中断，完全没有履行作为数据分析助手的职责。 【KIMI】模型仅执行了读取文件的操作，没有进行任何后续的数据处理和分析工作，因此无法满足任务要求。
困难难度评测结果
- 得分：62.0 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：
先读取完整数据，然后用一个 Python 脚本完成所有分析。 [read] [read]
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【KIMI】模型在意图追踪与变更处理方面表现较好，但在统计计算准确性、异常检测能力、图表选择与生成、报告输出完整性等方面表现一般，需要进一步优化和完善。
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