glm-5-turbo 在「CSV订单数据摘要」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：glm-5-turbo
- 用例名称：CSV订单数据摘要
- 测试类型：xsct-a
- 评测维度：文档问答
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） 请根据以上前10行数据回答： 1. 赵建国一共下了几笔订单？分别买了什么商品？ 2. 哪位客户有一笔订单处于"配送中"状态？对应的商品和金额是多少？ 3. 在这10行数据中，单笔总金额最高的订单是哪一笔？请给出订单编号、客户姓名和总金额。
任务要求
AI 模型需要满足以下要求：
- 准确识别赵建国（C001）在前10行中出现的3笔订单及对应商品（办公椅、墨盒×10、办公桌）
- 正确指出王鹏（C003）有一笔配送中的订单，商品为路由器，金额380元
- 正确识别单笔总金额最高的订单为ORD-2024-0804，客户王鹏，总金额3600元
- 回答结构清晰，按问题编号逐一作答
评测结果
综合得分
该模型在此用例的得分为：99.7 分（满分 100 分），已通过
基础难度评测结果
- 得分：99.7 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：
根据前10行数据，回答如下： **1. 赵建国一共下了 3 笔订单，分别购买了：** - 办公椅（2件，1,160元） - 墨盒×10（3件，135元） - 办公桌（1件，1,200元） **2. 处于"配送中"状态的客户是王鹏，对应的商品是路由器，总金额为 380 元。** **3. 单笔总金额最高的订单是：** - 订单编号：ORD-2024-0804 - 客户姓名：王鹏 - 总金额：3,600 元（购买显示器 2 台）
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出对三个问题的回答完全准确、信息完整、结构清晰，与参考答案高度吻合，是一份高质量的信息提取回答。 【GEMINI】模型表现优秀，完全符合任务要求。不仅准确提取了CSV中的关键信息，且逻辑清晰、表达准确，没有任何事实性错误或遗漏。 【KIMI】候选输出表现优秀，对CSV数据的理解和关键信息提取完全正确，三个问题的回答均准确无误，信息完整且结构清晰。 minor的格式差异不影响整体质量，是一组高质量的答案。
进阶难度评测结果
- 得分：64.3 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：
| Customer ID | Customer Name | Order Count | Completed Order Total | |-------------|---------------|-------------|-----------------------| | C003 | 王鹏 | 2 | 3,600 | | C002 | 李梅 | 3 | 2,820 | | C001 | 赵建国 | 3 | 2,495 | | C004 | 张晓燕 | 1 | 900 | | C005 | 陈伟 | 1 | 540 | **关于退款中订单的说明：** 李梅的已完成订单总金额不会发生变化，仍为 **2,820**。因为"退款中"的订单（ORD-2024-0805，键盘，320 元）当前状态并非"已完成"，在计算时并未被计入 2,820 这个数字。无论该订单最终退款成功与否，已完成订单的总金额都不受影响。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出在数字计算和排序方面表现良好，表头格式也符合要求，但最大缺陷是 Customer Name 列未将中文姓名翻译为英文拼音，导致翻译与格式规范维度严重失分。退款问题的回答逻辑有一定合理性，但未能完整覆盖参考答案要求的两种情况分析，结论过于单一。整体完成度中等偏下。 【GEMINI】模型在基础数据处理和表格呈现方面表现良好，但在执行翻译指令时不够彻底（未翻译姓名），且在处理假设性问题时逻辑过于僵化，未能按照题目设定的假设条件进行推演，导致追问回答部分得分较低。 【KIMI】英文表头符合要求（Customer ID / Customer Name / Order Count / Completed Order Total），表格呈现清晰。但存在严重问题：客户姓名完全未翻译，仍为中文；金额使用了千分位逗号分隔符，与参考示例的纯数字格式不一致。这些格式问题导致该维度仅达到及格线。
困难难度评测结果
- 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：
**血管参数对比分析 / Vascular Parameter Comparative Analysis** | 参数 / Parameter | 本研究（SCIP皮瓣·PTA）/ This Study (SCIP Flap · PTA) | 对比研究（DFA）/ Comparative Study (DFA) | |---|---|---| | 受区动脉 / Recipient Artery | 胫后动脉（PTA）/ Posterior Tibial Artery | 股深动脉（DFA）/ Deep Femoral Artery | | 受区动脉外径范围 / Recipient Artery External Diameter | 3.8–5.2 mm | 4.8–6.5 mm | | 供区血管蒂直径范围 / Donor Pedicle Diameter | 0.8–1.5 mm | 1.2–2.0 mm | | 管径比值范围 / Diameter Ratio Range | 2.8–5.0× | 2.5–4.5× | | 动脉切开口径倍数 / Arteriotomy Length Ratio | 3.0× | 3.5× | | 受区远端流量 / Distal Recipient Flow | >70 ml/min | >85 ml/min | | 皮瓣血流量范围 / Flap Perforator Flow | 12–22 ml/min | 18–28 ml/min | --- **分析结论 / Analysis Conclusions** **中文：** 1. **受区血管差异**：本研究选用PTA作为受区动脉，其外径（3.8–5.2 mm）明显小于对比研究中的DFA（4.8–6.5 mm），这与下肢不同解剖部位的血管解剖学特征一致。PTA位于小腿远端，血管口径天然较小。 2. **管径比值与吻合策略**：两组研究的管径比值范围相近（本研究2.8–5.0× vs. 对比2.5–4.5×），均处于改良端侧吻合的安全范围内。但对比研究采用了更大的动脉切开口径倍数（3.5× vs. 3.0×），结合其更大的受区血管口径，可能旨在进一步优化吻合口处的血流动力学条件。 3. **血流量差异**：对比研究的受区远端流量（>85 ml/min）和皮瓣血流量（18–28 ml/min）均高于本研究（>70 ml/min；12–22 ml/min），这与DFA作为更大口径的近端血管、血供更为充沛的解剖学基础相符。尽管绝对流量存在差异，本研究的皮瓣血流量仍维持在可靠范围内，8例皮瓣全部成活且随访期内无血管并发症，证实了在较小口径受区血管条件下，3.0倍切开口径的改良端侧吻合策略同样安全有效。 4. **总体评价**：两组数据共同表明，改良端侧吻合技术在不同口径的受区血管中均具有较好的适应性，切开口径倍数在3.0–3.5×区间内可兼顾层流维持与充分灌注。 **English:** 1. **Recipient Vessel Differences**: This study selected the PTA as the recipient artery, with an external diameter (3.8–5.2 mm) notably smaller than the DFA (4.8–6.5 mm) in the comparative study, consistent with the anatomical characteristics of different lower extremity sites. The PTA, located in the distal leg, inherently has a smaller caliber. 2. **Diameter Ratio and Anastomotic Strategy**: The two studies showed comparable diameter ratio ranges (2.8–5.0× vs. 2.5–4.5×), both falling within the safe zone for modified end-to-side anastomosis. However, the comparative study adopted a larger arteriotomy length ratio (3.5× vs. 3.0×), which — combined with its larger recipient vessel caliber — may have been intended to further...
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出在所有评分维度上均表现优秀。对比表格结构清晰，6个血管参数数值完全准确，中英双语标题和内容专业规范；对比分析结论有深度，不仅列举差异还给出了解剖学和临床背景解释；CSV数据附注整合自然，订单信息准确无误；多轮意图追踪到位，最终输出完全符合用户最新要求。整体是一份高质量的综合分析报告，几乎没有明显缺陷。 【GEMINI】该模型表现极其出色，不仅在数据提取和逻辑分析上展现了专业水准，还完美处理了多轮复杂的指令变更。在跨文档数据整合任务中，模型能够精准定位CSV数据并将其作为附注融入临床报告，体现了极强的指令遵循能力和逻辑整合能力。 【KIMI】该候选输出表现优异，在信息提取、双语质量、跨文档整合和多轮意图追踪四个维度均达到满分或接近满分。对比分析结论专业深入，结构清晰，医学术语使用规范。特别值得肯定的是：1）准确处理了用户多次变更的复杂意图；2）将看似无关的CSV数据以「数据完整性检查」的巧妙形式融入临床报告，既满足用户特殊需求又不破坏报告整体性；3）日文翻译段落专业准确。整体而言，这是一份高质量的综合分析输出。
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