Google: Gemma 4 31B 在「项目报告摘要撰写」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: Gemma 4 31B
  • 用例名称:项目报告摘要撰写
  • 测试类型:xsct-a
  • 评测维度:文档内容生成

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 请根据以上文档结构信息,帮我撰写第1章「执行摘要」的内容,要求: - 以正式的工作报告语气撰写 - 涵盖项目背景、Q3核心成果、关键风险、Q4展望四个方面 - 篇幅控制在300-500字 - 使用分段落形式,逻辑清晰

任务要求

AI 模型需要满足以下要求:

  1. 生成内容为正式工作报告语气,措辞专业得体
  2. 内容涵盖项目背景、Q3核心成果、关键风险、Q4展望四个方面
  3. 篇幅在300-500字之间
  4. 采用分段落形式,逻辑层次清晰
  5. 内容与2024年第三季度项目进展报告的主题一致

评测结果

综合得分

该模型在此用例的得分为:92.5 分(满分 100 分),已通过

基础难度评测结果

  • 得分:92.5 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:

[[reply_to_current]] 以下为您撰写的第1章「执行摘要」内容: **1. 执行摘要** 本报告旨在全面回顾2024年第三季度项目的整体进展情况,分析资源利用效率,并明确第四季度的核心工作方向。 在项目背景方面,本季度工作紧紧围绕年度战略目标展开,旨在通过优化产品运营流程与提升用户体验,进一步扩大市场份额并增强产品的核心竞争力。在复杂多变的市场环境下,项目组通过精准的资源配置与高效的执行力,确保了各项关键指标的稳步推进。 Q3期间,项目取得了显著的阶段性成果。核心里程碑任务均按计划节点完成,重点功能模块已成功上线并进入迭代优化期,关键性能指标(KPI)达成率超出预期。通过对运营链路的深度优化,用户活跃度与留存率均实现了环比增长,初步验证了本阶段产品策略的有效性。 尽管进展顺利,但项目在推进过程中仍面临一定的挑战。主要风险集中在跨部门协作的沟通成本较高以及部分第三方供应商交付周期波动等问题。针对上述风险,项目组已建立快速响应机制,并通过优化供应商管理流程,有效降低了对整体进度的影响。 展望第四季度,项目将进入冲刺阶段。工作重点将聚焦于Q3成果的规模化推广及深层数据挖掘,旨在通过精细化运营实现用户增长的二次突破。同时,我们将重点攻坚遗留的性能瓶颈,确保在年度验收前交付一个高稳定性、高满意度的产品版本。

AI 评审点评

以下是 AI 评审对该模型输出的点评:

【KIMI】整体来看,生成的执行摘要质量很高,很好地满足了任务的各项要求,表现出色。

进阶难度评测结果

  • 得分:— 分
  • 通过状态:未通过

AI 评审点评

以下是 AI 评审对该模型输出的点评:

模型返回空输出,已跳过 AI 评分(finish_reason=stop)

困难难度评测结果

  • 得分:90.0 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:

call:write{content: "**收件人**:各部门经理及以上管理人员 **发件人**:产品运营部 **主题**:关于召开2024年第三季度项目总结会议的通知 各位领导: 为全面回顾Q3项目进展并部署Q4重点工作,经研究决定召开2024年第三季度项目总结会议,现将有关事项通知如下: **一、会议时间** 下周三(具体日期)下午14:00 **二、会议形式** 线上会议(腾讯会议) 会议号:886-2450-7731 密码:2024 **三、参会人员** 各部门经理及以上级别管理人员 **四、会议背景** Q3期间,团队在多个维度取得积极进展: - 核心里程碑按计划顺利完成,项目整体交付情况良好 - 资源配置持续优化,成本管控成效显著 - 跨部门协作效率大幅提升,项目沟通周期明显缩短 - 风险预警机制有效运行,关键问题得到妥善处置 - Q4冲刺计划已明确方向,收官阶段各项准备工作稳步推进 **五、会议议程** 1. Q3项目执行情况汇报 2. 资源与成本分析 3. 风险复盘与经验总结 4. Q4工作计划发布与讨论 **六、相关要求** 请各位参会人员合理安排工作,确保准时出席。如有特殊情况无法参加,请提前向分管领导报备。 **七、保密提醒** 本次会议内容涉及尚未公开的经营数据及战略规划信息,所有参会人员对会议内容负有保密义务,未经授权不得以任何形式向外部或非参会人员透露。如有违反,将依据公司保密制度追究相关责任。 产品运营部 2024年X月X日",file: "meeting_notice_final.md"}

AI 评审点评

以下是 AI 评审对该模型输出的点评:

【KIMI】模型整体表现优秀,能够准确追踪和执行多轮变更指令,正确保存文件,邮件内容质量高,风格适配,细节准确。

相关链接

您可以通过以下链接查看更多相关内容:

加载中...