MiniMax-M2.7 在「报告章节摘要提取」的评测结果

基本信息

• 模型名称：MiniMax-M2.7
• 用例名称：报告章节摘要提取
• 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文档 `project_report.docx` 摘要： **文档标题**：2024年第三季度项目进展报告 **作者**：产品运营部 **字数**：约 3200 字 **章节结构**： 1. 执行摘要 2. 项目背景与目标 3. Q3 主要里程碑完成情况 4. 资源投入与成本分析 5. 风险与问题记录 6. Q4 工作计划 7. 附件：数据支撑材料 以下是文档第4章「资源投入与成本分析」的内容： 本季度项目总预算为 850 万元，实际支出 792 万元，预算执行率为 93.2%。其中人力成本占比最高，达 58%（约 459 万元），主要用于核心研发团队 32 人的薪酬及外包测试团队 15 人的费用；硬件与云服务费用占比 27%（约 214 万元），包括新增 3 台 GPU 服务器采购及阿里云 ECS 实例扩容；其余 15% 为差旅、培训及行政支出。与 Q2 相比，总支出增长 12%，主要原因是 8 月份紧急引入外包团队应对交付压力。成本节约方面，通过优化 CI/CD 流水线减少了约 18 万元的云资源浪费。 请帮我回答以下问题：这一章节中，本季度的预算执行率是多少？人力成本具体包含哪些组成部分？与上季度相比支出变化的主要原因是什么？

任务要求

AI 模型需要满足以下要求：

1. 准确回答预算执行率为93.2%
2. 明确指出人力成本包含核心研发团队32人薪酬和外包测试团队15人费用两部分
3. 说明与Q2相比总支出增长12%，主要原因是8月份紧急引入外包团队应对交付压力
4. 回答结构清晰，逐一对应三个问题

评测结果

综合得分

该模型在此用例的得分为：99.3 分（满分 100 分），已通过

基础难度评测结果

• 得分：99.3 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：

用户询问的是关于文档第4章「资源投入与成本分析」的几个具体问题。让我根据提供的摘要内容来回答： 1. 预算执行率是多少？→ 93.2% 2. 人力成本包含哪些组成部分？→ 核心研发团队32人的薪酬 + 外包测试团队15人的费用 3. 与上季度相比支出变化的主要原因？→ 总支出增长12%，主要原因是8月份紧急引入外包团队应对交付压力 这些都是直接可以从提供的文本中提取的信息。 根据文档第4章内容，回答如下： **1. 预算执行率** 本季度预算执行率为 **93.2%**（实际支出 792 万元 / 总预算 850 万元）。 **2. 人力成本的组成部分** 人力成本（约 459 万元，占比 58%）包含两部分： - 核心研发团队 **32 人**的薪酬 - 外包测试团队 **15 人**的费用 **3. 与上季度相比支出变化的主要原因** 与 Q2 相比，总支出增长 **12%**。主要原因：**8 月份紧急引入外包团队以应对交付压力**。 此外，文档还提到了一项成本节约措施：通过优化 CI/CD 流水线，减少了约 **18 万元**的云资源浪费。

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，准确、完整地回答了用户提出的三个问题，关键数据提取无误，结构清晰，逻辑层次分明。额外补充了CI/CD优化节省云资源的信息，为回答增添了价值而不显冗余。整体质量达到高水准，完全符合参考答案的要求。 【GEMINI】模型表现优秀，能够精准地从给定文档中提取核心信息，并以清晰、结构化的方式回答用户提出的所有问题。在信息准确性、完整性和表达清晰度方面均达到了极高标准。 【KIMI】该候选输出表现优秀，准确、完整、清晰地回答了用户提出的三个问题。信息提取零误差，结构组织合理，关键数据突出，完全符合任务要求。模型在回答中额外补充的成本节约信息属于原文事实，不影响评分质量。

进阶难度评测结果

• 得分：92.3 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：

The user wants me to: 1. Translate the 7 chapter names and their descriptions into English in a table format 2. Write a concise English summary paragraph (under 100 words) summarizing the Q3 report's key value Let me provide this based on the chapter information I already have. | Chapter Name | Description | |---|---| | Executive Summary | A high-level overview of the entire report, enabling senior management to quickly grasp the full picture. | | Project Background & Objectives | Outlines the project rationale, business context, and expected goals. | | Q3 Major Milestone Progress | Lists the key deliverables planned for Q3 and reports on their actual completion status. | | Resource Allocation & Cost Analysis | Summarizes investment in human resources, funding, etc., and provides comparative cost analysis. | | Risks & Issues Log | Documents risk factors and unresolved issues encountered during project execution. | | Q4 Work Plan | Outlines priorities and tasks planned for the fourth quarter. | | Appendix: Supporting Data | Provides supplementary data and charts that substantiate conclusions in the main text. | --- **Summary Paragraph** This Q3 Progress Report provides a comprehensive review of project performance, covering milestone completion, resource allocation, cost management, and risk tracking. It offers stakeholders a clear view of current status and existing challenges. The report serves as a critical baseline for Q4 planning, enabling the team to prioritize unresolved issues, optimize resource deployment, and set realistic goals — ensuring sustained momentum toward year-end objectives.

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出整体质量较高，完整完成了用户的两项任务：7行英文表格章节顺序正确、翻译准确；英文摘要简洁专业、涵盖核心内容并提及Q4指导意义。与参考答案相比，翻译措辞略有差异但语义等价，摘要内容稍简但符合要求。格式清晰，表格与摘要分开呈现，整体回答结构良好，适合作为商务邮件素材使用。 【GEMINI】模型出色地完成了任务，不仅准确翻译了文档结构，还撰写了高质量的商务摘要。内容组织逻辑严密，完全符合用户提出的所有格式和内容约束。 【KIMI】候选输出整体质量优秀，完整完成了用户要求的两个任务。表格翻译准确完整，摘要简洁专业且涵盖核心要点。 minor不足在于摘要未明确标注报告编制部门，以及存在轻微的HTML实体编码和think标签残留问题，但不影响实质内容的正确性和可用性。

困难难度评测结果

• 得分：89.8 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：

The user is asking me to clarify the calculation logic for the "全年预算缺口预计达73万元" figure and then do a new calculation assuming Q4 server costs also exceed by 20%. Let me re-examine the document: **Q3 Budget vs Actual:** | 项目 | 预算（万元） | 实际（万元） | 偏差 | |------|------------|------------|------| | 人力成本 | 180 | 195 | +8.3% | | 服务器与云资源 | 60 | 72 | +20% | | 外包费用 | 40 | 38 | -5% | | 其他 | 20 | 18 | -10% | | 合计 | 300 | 323 | +7.7% | So Q3 exceeded by 23万元. **My original calculation for 73万元:** Q3超支 23万 + Q4追加申请 50万 = 73万 Wait, this doesn't quite make sense as a "预算缺口" (budget gap). Let me re-read what I wrote: "Q3实际成本较预算超支23万元（+7.7%），叠加Q4追加申请的50万元，全年预算缺口预计达73万元." I added the Q3 overage directly to the Q4 additional request, but that's not the right way to think about it. The Q4 request is asking for additional budget on top of what's already planned, so if I treat the 50万 as a new request and add it to Q3's 23万 overage, that gives 73万 total additional funding needed beyond the original 300万 budget. But I need to clarify whether the 50万 is meant to cover Q4's own overspend or if it's a separate supplemental request. the Q3 actual total of 323万元 as the baseline, then adding Q4's planned 300万元 plus the 50万元 supplemental request gets us to 673万元 total for the year. But that doesn't quite capture what the user is asking about. Let me recalculate: the 73万元 figure comes from Q3's 23万元 overspend plus Q4's 50万元 supplemental request, which assumes Q4 follows the original 300万元 budget without additional overruns. Now I'm looking at what happens if server costs in Q4 exceed budget by 20% — if the original server allocation was 60万元, a 20% overage would add another 12万元 on top of Q4's planned amount. 预算 = 50万（追加申请） 全年总缺口 = 23万 + 50万 + 12万 = 85万 So the full-year budget shortfall would be 85万元 if Q4 server costs also exceed by 20%, compared to the original 600万 total budget (300万 Q3 + 300万 Q4). I see the issue now—my original 73万元 calculation was conflating Q3's actual overspend with Q4's...

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型整体表现良好，核心计算数字（73万拆解、72万服务器成本、12万额外超支、85万总缺口）均正确，分步骤推算过程基本完整。主要不足在于：在解释73万元时额外引入了673万的「严格」计算，这一部分逻辑存在混淆（将Q3超支和Q4追加预算重复计入全年预算），且与参考答案的预期解释方向不完全一致，可能对用户造成误导。若去掉这一额外的「严格」计算，直接按参考答案的逻辑（Q3超支23万+Q4追加50万=73万）解释，回答会更加简洁准确。 【GEMINI】模型表现优秀。在面对用户对计算逻辑的质疑时，模型能够客观审视之前的表述，通过严谨的步骤拆解重新梳理了财务数据，计算准确且逻辑清晰，完美满足了用户的所有指令要求。 【KIMI】该回答整体质量较高，核心计算准确，能够分步骤展示推算过程，并保持与上下文的良好一致性。主要不足在于自我修正时造成的逻辑绕弯，以及部分表述上的重复和术语混用。建议在类似场景中更直接地回应用户问题，避免过度自我质疑导致阅读困惑。

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：「报告章节摘要提取」
• 查看该模型的所有评测结果：MiniMax-M2.7
• 浏览同维度的其他用例：「文档问答」
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