Google: Gemini 3.1 Pro Preview 在「项目报告核心概括」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：Google: Gemini 3.1 Pro Preview
- 用例名称：项目报告核心概括
- 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 请用简明扼要的语言概括这份文档的核心要义。
任务要求
AI 模型需要满足以下要求：
- 概括内容需涵盖文档的主题（Q3项目进展报告）
- 需提及文档的关键组成部分，如里程碑完成情况、成本分析、风险记录、Q4计划等
- 语言简明扼要，避免冗长，总结控制在合理篇幅内
- 不得编造文档中未提及的具体数据或结论
评测结果
综合得分
该模型在此用例的得分为：80.7 分（满分 100 分），已通过
基础难度评测结果
- 得分：80.7 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：
这份文档的核心要义可以概括为：**复盘Q3，规划Q4**。 具体而言，这是一份由产品运营部出具的季度管理报告，主要目的在于： 1. **回顾总结总结**：全面评估2024年第三季度项目的执行情况，包括目标达成度、资金/资源消耗以及遇到的风险问题。 2. **指引下一步工作**：基于Q3的执行结果与数据支撑，明确第四季度的重点工作计划，为项目的持续推进提供管理和决策依据。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出整体质量中等偏上，能够抓住文档的核心主旨并以简洁结构呈现。主要不足在于：内容覆盖不够全面，对「里程碑完成情况」等关键章节未明确提及；存在「回顾总结总结」的文字重复错误，影响表达准确性。若能逐一点到各主要章节并修正笔误，质量将有明显提升。 【GEMINI】模型表现出色，能够快速抓住文档的核心要义并进行高度概括。语言凝练，逻辑清晰，虽然在细节覆盖上不如参考答案详尽，但作为一份「简明扼要」的概括，其表现完全符合任务要求。 【KIMI】该模型输出基本完成了概括文档核心要义的任务，「复盘Q3，规划Q4」的提炼较为精准，语言简洁。但存在内容覆盖不够完整（遗漏里程碑完成情况、附件说明）、表达不够准确（成本分析/风险记录的泛化处理、「回顾总结总结」的笔误）等问题。整体达到及格水平，但距离优秀还有提升空间，建议加强对文档章节结构的全面把握和用词准确性。
进阶难度评测结果
- 得分：90.8 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：
1. Q3项目整体完成率达87%，预算控制良好，结余18万元。 2. 用户增长与体验优化按期交付，月活破520万，NPS达标。 3. 数据中台因技术选型延期两周，计划10月上线并推进Q4目标。 该报告最突出的风险项是数据中台项目因技术选型争议导致的延期风险。
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好，格式严格遵从要求，3个编号要点均未超过30字，风险项识别准确。主要不足在于内容维度划分上，将预算结余与完成率混合在要点1，导致成本/资源维度（尤其是ROI数据）未能得到充分体现；此外风险补充句未涉及应对措施，略显简略。总体而言是一份合格的精炼概括，基本满足任务要求。 【GEMINI】模型完美执行了指令要求，不仅准确概括了文档核心要义，且在格式限制、字数控制及风险识别方面表现出色，符合专业评测标准。 【KIMI】该候选输出整体质量较高，严格遵循了格式要求，3个要点覆盖了核心维度，风险识别准确。主要改进空间在于：第1点可补充ROI数据提升完整性，第3点对Q4计划的概括可更具体，风险说明句可进一步精简。总体而言是一份合格的精炼概括。
困难难度评测结果
- 得分：79.88 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：
我已经为你生成了中英双语简报，并按照要求处理了所有的细节限制（包括保留风险等级及Q4影响标注、英文部分不超过500字、以及在英文部分隐去了节余百分比）。 我现在将内容写入到 `briefing_q3.md` 文件中。 ```bash cat briefing_q3.md ## 核心摘要 2024年Q3，产品运营部的一体化数字运营平台项目整体进展顺利。三大模块中，用户增长模块V2.0提前上线且DAU提升18%，数据分析看板原型按期交付并获评优秀。但供应链管理模块因第三方接口联调问题延迟两周进入UAT。成本方面，实际支出817万元，低于预算852万元，节余约4.1%。Q4计划重点为供应链模块灰度发布、数据看板正式上线及全平台集成测试。 ## 风险分析 - **高风险**：供应链模块第三方接口稳定性不足。 - **应对措施**：已启动备选供应商评估。 - **⚠️ 影响Q4交付**：是，将直接影响10月供应链模块的灰度发布。 - **中风险**：核心开发人员离职风险（2人提出离职意向）。 - **应对措施**：已启动内部轮岗与外部招聘。 - **⚠️ 影响Q4交付**：是，人员缺口可能影响Q4多模块并行推进。 - **低风险**：数据分析模块在大数据量场景下响应偏慢。 - **应对措施**：计划Q4进行性能优化。 - **⚠️ 影响Q4交付**：可能，若优化工作量超预期，将影响11月数据看板正式上线。 --- ## Core Summary In Q3 2024, the integrated digital operations platform project by the Product Operations Department progressed smoothly overall. Among the three major modules, the User Growth Module V2.0 was launched ahead of schedule, boosting DAU by 18%. The Data Analysis Dashboard prototype was delivered on time and rated as excellent. However, the Supply Chain Management Module was delayed by two weeks entering UAT due to third-party interface integration issues. Regarding costs, actual expenditure was 8.17 million yuan, which was under the total budget of 8.52 million yuan. Q4 plans focus on the gray release of the supply chain module, the official launch of the data dashboard, and full-platform integration testing. ## Risk Analysis - **High Risk**: Insufficient stability of the third-party interface in the supply chain module. - **Countermeasure**: Alternate supplier evaluation has been initiated. - **⚠️ Impact on Q4 Delivery**: Yes, it will directly affect the gray release of the supply chain module in October. - **Medium Risk**: Risk of core developers resigning (2 employees expressed intention to leave). - **Countermeasure**: Internal job rotation and external recruitment have been initiated. - **⚠️ Impact on Q4 Delivery**: Yes, the manpower shortage may affect the parallel advancement of multiple modules in Q4. - **Low Risk**: Slow response of the data...
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型整体上正确理解了多轮对话的意图变更，信息提取准确，中英双语内容基本对应，矛盾指令（节余百分比中英差异）处理正确。主要问题有两点：一是未使用专用write工具而是用bash命令模拟写入，违反了系统提示的工具使用规范；二是输出文件缺少顶级标题，结构不够完整。英文词数控制在500词以内，风险分类和Q4影响标注均完整。综合来看，内容质量较好，但工具调用规范性和格式完整性有明显不足。 【KIMI】模型基本理解了三轮意图变更（概括→风险提取→合并双语简报），但在最终合并输出时存在明显问题：用户明确要求「中文在前，英文在后，两部分内容一一对应」且「简报分为两个板块：'核心摘要'和'风险分析'」，但模型输出的是中文摘要+中文风险+英文摘要+英文风险的混合结构，而非先完整中文板块再完整英文板块的结构。此外，矛盾指令（中英文节余数据差异）处理正确，英文部分确实移除了4.1%节余数据。 【GEMINI】模型表现出色，不仅准确理解了复杂的任务流转，还完美处理了针对中英文内容的差异化指令。在信息提取、格式控制及工具使用方面均表现出专业水准。
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