glm-5-turbo 在「个人陈述口语转书面」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：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：
- 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
- 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
- 不得凭空添加原文未提及的经历、数据或成就
- 语法正确，用词精准，逻辑衔接自然紧凑
- 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：92.8 分（满分 100 分），已通过
基础难度评测结果
- 得分：92.8 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：
以下是润色后的版本： > While I have not yet had the opportunity to engage in hands-on laboratory research, I have built a consistent record of achievement through inter-university competitions throughout my undergraduate studies. A particularly formative experience was participating in a regional debate competition. Having been naturally reserved, I had often found it challenging to advocate for my own ideas, even in collaborative settings. Recognizing upon entering university that this tendency was limiting my potential, I deliberately sought opportunities to overcome it. This process of self-directed growth has significantly strengthened my ability to articulate and defend my viewpoints with confidence. I view the master's program as an ideal environment in which to further develop my leadership capacity. 主要调整说明： - **开头衔接**：用 "While I have not yet had the opportunity…" 替代直白的 "Although I do not have…"，将"没有实验室经验"从一种劣势表述转化为"尚未获得的机会"，语气更积极。 - **去口语化**："Growing up, I was quite introverted" → "Having been naturally reserved"；"holding me back" → "limiting my potential"；"push past it" → "deliberately sought opportunities to overcome it"——均替换为更正式的学术申请措辞。 - **逻辑收紧**：原文中"内向→大学意识到问题→决定改变→现在自信→硕士项目"的链条较为松散，润色后用 "Recognizing… I deliberately sought…" 和 "This process of self-directed growth has…" 将因果关系显性化，使叙事弧线更完整。 - **结尾升华**："keep building my leadership abilities" 改为 "further develop my leadership capacity"，避免 "keep building" 的随意感，同时 "capacity" 比 "abilities" 更贴合学术语境中对潜力的强调。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出整体表现优秀，完整保留原文信息点，语言质量提升明显，风格符合硕士申请个人陈述的正式学术语体，段落逻辑衔接紧凑。附带的「主要调整说明」部分展示了清晰的润色思路，对每处改动均有合理解释，体现了较强的语言意识。与参考答案相比，主要差距在于个别句式的精炼程度和时间维度的层次感略有不足，但整体已达到高质量申请文书的标准。 【GEMINI】模型出色地完成了润色任务，不仅在语言层面实现了从口语到学术风格的完美转换，还通过对逻辑结构的优化，使个人陈述更具说服力。模型对指令的遵循度极高，既保证了信息的完整性，又显著提升了文稿的专业水准。 【KIMI】该候选输出是一份高质量的学术申请文书润色成果。在严格保留原文所有信息点的基础上，成功将口语化、松散的叙述转化为正式、紧凑的学术英语段落。语言层面的提升尤为突出，词汇选择精准，句式结构多样，语气把握恰当。结构安排上，叙事弧线清晰完整，从自我认知的局限到主动寻求改变，再到成长收获与未来期望，层层递进。 minor 的优化空间在于个别添加的修饰语（如「self-directed」）可更贴近原文的简洁风格，但整体已达到硕士申请个人陈述的专业水准。
进阶难度评测结果
- 得分：94.6 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，整体成本控制良好，基本未超出预算框架，仅个别细分领域出现小幅超支。技术层面虽在推进过程中遇到若干挑战，但均已妥善解决。展望第四季度，团队将持续推动新功能上线，进一步优化用户体验，力争在产品竞争力上实现新的突破。同时需关注的是，鉴于本季度技术推进中暴露的潜在隐患，Q4在新功能交付节奏与系统稳定性之间仍需保持审慎平衡，防范技术风险对整体目标的扰动。
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，完整满足了用户的所有调整要求：将「约三成」改为「约30%」、新增Q4技术风险提示、保持正式书面语风格、字数在规定范围内。Q4风险提示部分的表达（「在新功能交付节奏与系统稳定性之间仍需保持审慎平衡，防范技术风险对整体目标的扰动」）甚至比参考答案更具专业深度，体现了对高管报告语境的良好把握。各维度表现均衡，是一份高质量的润色输出。 【GEMINI】模型表现出色，完美执行了所有指令要求。润色后的文本既保持了原文的逻辑主线，又通过正式的商务用语提升了专业度，且在字数限制、数字格式调整及风险提示逻辑上均表现精准，完全符合高管汇报的质量标准。 【KIMI】该候选输出是一份高质量的高管层汇报文本，完整满足所有功能要求和约束条件。语言正式得体，信息保留完整，约束满足度高，输出规范简洁。唯一可优化之处是结尾风险提示句稍长，可更凝练，但不影响整体质量。
困难难度评测结果
- 得分：31.9 分
- 通过状态：未通过
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]]
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】candidate_output 实质上是一个空响应，仅包含运行时回复标签「[[reply_to_current]]」，没有执行任何文件编辑操作，也没有输出修改后的文本内容。四个评分维度全部无法达标。这是一次完全失败的响应，模型未能对用户的明确修改请求做出任何有效处理。 【GEMINI】模型表现优秀，完美执行了所有指令。在多轮对话约束叠加的情况下，不仅保持了对之前输出的一致性，还通过 edit 工具实现了精准的局部修改，完全符合专业商务报告的润色要求。 【KIMI】候选输出完全失败。用户明确要求使用edit工具对project_report.docx进行两处精确修改，但模型仅返回了一个空回复标记「[[reply_to_current]]」，未执行任何实际操作，未输出任何修改后的文本，也未调用任何工具。这是严重的任务失败，所有评分维度均不得分。
相关链接
您可以通过以下链接查看更多相关内容：
