Google: Gemma 4 26B A4B 在「个人陈述口语转书面」的评测结果

基本信息

• 模型名称：Google: Gemma 4 26B A4B
• 用例名称：个人陈述口语转书面
• 测试类型：xsct-a
• 评测维度：文档润色与优化

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 --- 我正在准备硕士申请的个人陈述，下面这段话写得比较口语化、结构也比较松散，请帮我润色成正式的学术申请风格英文。要求： 1. 保留所有原始信息点，不要添加没有提到的经历或成就； 2. 语气正式、自信但不夸张； 3. 逻辑衔接更紧凑，段落结构更清晰； 4. 修正任何语法或用词不当之处。 原文如下： "Although I do not have hands-on laboratory research experience, I bring a solid record of competition-based achievements. Throughout my undergraduate years, I took part in multiple inter-university contests. The turning point came when I joined a regional debate competition. Growing up, I was quite introverted and often struggled to speak up for my own ideas, even in work-like situations. When I started college, I realized this was holding me back, so I decided to push past it. Now I feel much more confident when I present my views, and I believe the master's program will give me the right setting to keep building my leadership abilities."

任务要求

AI 模型需要满足以下要求：

1. 输出为完整的润色后英文段落，风格符合硕士申请个人陈述的正式学术语体
2. 保留原文所有信息点：无实验室经历、竞赛成绩、区域辩论赛经历、曾经内向、大学期间决心改变、现在更自信、期望硕士项目提升领导力
3. 不得凭空添加原文未提及的经历、数据或成就
4. 语法正确，用词精准，逻辑衔接自然紧凑
5. 语气自信而不浮夸，避免过度使用形容词或空泛表述

评测结果

综合得分

该模型在此用例的得分为：92.0 分（满分 100 分），已通过

基础难度评测结果

• 得分：92.0 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：

为了符合硕士申请（Personal Statement）的学术规范，润色重点在于：将“个人成长叙事”转化为“能力素质证明”，将“口语化的描述”转化为“专业化的表达”。 以下为你提供两个版本的建议： ### 版本一：稳重学术风 (Formal & Academic) 这个版本最适合大多数主流院校。它将你的性格转变描述为一种“主动的自我驱动力（Self-driven development）”，并将辩论赛提升为“逻辑思维与沟通能力”的体现。 > "While my background does not include direct laboratory research experience, I have established a strong track record of success through competitive academic and extracurricular engagements. During my undergraduate studies, I actively participated in various inter-university competitions, a journey that proved transformative. Notably, my involvement in a regional debate competition served as a pivotal milestone in my personal and professional development. Having previously struggled with introversion and the articulation of my ideas, I proactively sought challenges to refine my communication skills. This intentional growth has significantly enhanced my ability to present complex perspectives with confidence. I am now eager to leverage the rigorous environment of this Master’s program to further cultivate my analytical reasoning and leadership potential." ### 版本二：精炼有力风 (Concise & Impactful) 如果你的申请文书有严格的字数限制，这个版本更直接，通过更高级的动词（如 *cultivated*, *transitioned*, *demonstrated*）来增强力量感。 > "Although I lack formal laboratory experience, I possess a proven ability to excel in high-pressure competitive environments. My participation in multiple inter-university contests, most notably a regional debate competition, marked a significant turning point in my development. I transitioned from an introverted student who hesitated to voice opinions into a confident communicator capable of articulating well-reasoned arguments. This process of self-improvement demonstrates my proactive approach to overcoming challenges. I look forward to bringing this resilience and growing leadership capacity to the [Program Name] community, where I aim to further refine my professional competencies." --- ### 💡 润色要点解析（为什么这么改）： 1. **弱化“劣势”，强化“潜力”**： * **原文**：*“I do not have hands-on...

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】这是一次高质量的润色。模型不仅完美执行了所有指令要求，提供了两个不同风格的高质量版本，还附带了详细的修改解析，帮助用户理解如何将口语转化为正式语体。在保留原意的前提下，极大地提升了文本的专业性和说服力。 【KIMI】整体来看，这个润色后的段落很好地满足了硕士申请个人陈述的要求，在保留原文信息的基础上，通过提升语言质量、适配申请风格、优化结构衔接，使段落更加正式、自信、有说服力。虽然在结构和衔接上还有提升空间，但整体表现已经非常出色。

进阶难度评测结果

• 得分：95.0 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：

本季度，团队紧密围绕既定核心目标稳步推进各项工作，主要里程碑均已按计划顺利达成。用户规模实现显著增长，环比增幅约30%。在资源投入方面，整体成本控制处于合理区间，基本维持在预算范围内，仅个别细分领域出现小幅超支。技术层面虽在推进过程中遭遇若干技术瓶颈，但均已通过应急处置予以解决。展望第四季度，团队将持续推动新功能上线，致力于进一步优化用户体验；同时，需高度关注技术架构稳定性及潜在的技术迭代风险，以确保业务平稳运行。

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】该模型表现优秀，能够精准捕捉口语化初稿的核心原意，并将其重构为高质量、职业化的商务书面表达。在特定约束（如百分比形式转换、风险提示延伸）方面执行到位。唯一的小瑕疵是字数略微超出了上限（约209字），但在内容完整性和风格适配度上表现出色。 【KIMI】整体来看，该润色版本较好地满足了各项要求，保留了原文核心信息，语言风格正式规范，同时满足了字数、数字表达形式和新增风险提示等约束，输出格式规范，表现优秀。

困难难度评测结果

• 得分：75.8 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：

call:edit{edit:"replace",file:"project_report.docx",new_text:"# 1. 执行摘要\n\n本季度，团队围绕既定核心目标稳步推进，各项关键指标总体达成预期。\n\n**用户增长方面**，Q3新增用户12万人，环比增长30%，增长主要得益于暑期专项推广活动的有效拉动。\n\n**产品迭代方面**，本季度累计发布3个大版本，修复缺陷200余项，用户体验满意度显著提升。\n\n**成本概况方面**，Q3总支出450万元，因服务器扩容预估偏差导致小幅超支，目前已启动成本优化方案。\n\n**风险提示方面**，当前最突出的风险为核心研发人员流失问题——本季度已有3名高级工程师离职，亟需在Q4制定针对性的人才保留方案。\n\n**总结与展望**，综合来看，Q3整体表现基本符合预期，但Q4面临较大挑战，尤其是年度冲刺目标的达成压力较为突出，需提前做好资源调配与风险应对准备。",old_text:"# 1. 执行摘要\n\n本季度，团队围绕既定核心目标稳步推进，各项关键指标总体达成预期。\n\n**用户增长方面**，Q3新增用户约12万人，环比增长约30%，增长主要得益于暑期专项推广活动的有效拉动。\n\n**产品迭代方面**，本季度累计发布3个大版本，修复缺陷逾200项，用户体验满意度显著提升。\n\n**成本概况方面**，Q3总支出约450万元，略超预算，超支部分主要源于服务器扩容成本的预估偏差。\n\n**风险提示方面**，当前最突出的风险为核心研发人员流失问题——本季度已有3名高级工程师离职，亟需在Q4制定针对性的人才保留方案。\n\n**总结与展望**，综合来看，Q3整体表现基本符合预期，但Q4面临较大挑战，尤其是年度冲刺目标的达成压力较为突出，需提前做好资源调配与风险应对准备。"}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】模型虽然完成了用户指出的两项具体修改任务（将“超200项”改为“200余项”，并为成本超支增加了归因和对策），但在多轮对话的复杂约束遵循上表现较差。特别是严重违反了字数限制（150字以内），且未能按要求修正语气弱的词汇（保留了被点名批评的“小幅超支”），同时也未能彻底清理“基本”、“总体”等模糊词。在工具使用上，虽然调用正确，但修改范围不够精确。 【KIMI】整体来看，模型在精确修改、意图追踪和工具使用规范性方面表现较好，基本满足了任务要求。但在润色质量与约束满足方面还有提升空间，尤其是在字数控制上需要更加严格。

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：「个人陈述口语转书面」
• 查看该模型的所有评测结果：Google: Gemma 4 26B A4B
• 浏览同维度的其他用例：「文档润色与优化」
• 返回排行榜首页