kimi-k2.5 在「学术长句润色」的评测结果

基本信息

• 模型名称：kimi-k2.5
• 用例名称：学术长句润色
• 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 请帮我润色以下段落，这段话出现在报告第5章「风险与问题记录」中。要求保持学术书面语风格，提升句子的清晰度和可读性，但不能改变原意。原文如下： This phenomenon might be attributed to the fact that the standardized deployment of resource optimization strategies and redundancy failover mechanisms across the project portfolio, which could have effectively counteracted the operational disruptions ordinarily precipitated by budget constraints and personnel turnover, thereby attenuating their discernible influence during the quarterly risk assessment.

任务要求

AI 模型需要满足以下要求：

1. 润色后的文本必须完整保留原文的核心语义：标准化的资源优化策略和冗余容灾机制抵消了预算限制和人员流动带来的运营中断，从而在季度风险评估中减弱了这些因素的可见影响
2. 润色后的文本应为正式学术书面语风格，避免口语化表达
3. 应提升原文的清晰度和可读性，例如拆分过长从句、减少不必要的修饰词、使逻辑层次更分明
4. 润色结果仍为英文

评测结果

综合得分

该模型在此用例的得分为：— 分（满分 100 分），未通过

基础难度评测结果

• 得分：— 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：

我先查看一下工作区中的文档，了解上下文后再进行润色。ls -la [[reply_to_current]]read:0>{"file": "project_report.docx"}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型完全未完成任务。候选输出仅包含尝试通过工具读取工作区文件的操作（ls 和 read 调用），而用户已在提示中明确提供了需要润色的原文段落，无需额外读取文件。模型应直接对所提供的英文段落进行润色改写，但实际上没有输出任何润色结果。这是一次完全失败的响应，三个评分维度均为0分。 【GEMINI】模型在处理指令时出现了严重的任务理解偏差。用户明确要求对提供的段落进行润色，但模型却将其误解为需要先读取工作区文件，直接跳过了核心润色任务，导致输出结果完全不符合预期。 【KIMI】该候选输出完全失败。用户明确要求润色一段英文文本，并提供了完整的上下文（包括文档摘要和具体段落），但模型仅执行了工具调用（ls和read）来查看文件，随后停止响应，完全没有输出任何润色后的文本。这是一个典型的任务未完成错误——模型误解了任务边界，以为需要先读取文件才能回答，但实际上用户已经在对话上下文中完整提供了需要润色的原文。模型应当直接基于提供的原文进行润色，而非调用工具。参考答案展示了优秀的润色范例：将超长复合句拆分为两句、去除冗余表达、简化复杂措辞，同时完整保留核心语义。候选输出未能完成基本任务要求。

进阶难度评测结果

• 得分：5.2 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：

我需要先读取文档，找到第5章中对应段落的位置。请稍等。read:0>{"file_path": "/workspace/project_report.docx"}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出仅停留在尝试读取文档的初步阶段，既未生成任何润色文本，也未完成 edit 工具调用将结果写入文档。整体任务几乎完全未完成，与参考答案要求相差甚远。 【GEMINI】模型在接收到指令后，仅执行了读取文件的初步操作，未能根据用户要求完成文本润色及写入文件的任务。当前输出处于任务执行的起始阶段，未达到交付标准。 【KIMI】候选输出完全失败。模型没有理解任务的核心要求：用户已经提供了原文和润色要求，期望模型直接输出润色后的文本并使用edit工具写入文件。但模型仅输出了读取文件的意图，且工具调用格式错误，未产生任何实质性的润色结果。这是一个典型的任务理解失败案例，模型将简单的文本润色任务复杂化为不必要的文件读取操作，且未响应用户关于'直接写入'的明确要求。

困难难度评测结果

• 得分：84.1 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：

我将按照您的要求准备两段文字，并修正医学逻辑关系（抗凝药物主要作用于凝血通路而非直接改善静脉淤滞的血流动力学），同时保持谨慎的学术语气。然后直接写入文档的对应位置。 **第5节（讨论段落）：** "This phenomenon could potentially be explained by the concomitant use of lipid-lowering and anticoagulant therapies among study participants. Statin therapy may have attenuated lipid-induced arterial endothelial injury, while anticoagulation could have mitigated thrombotic risks associated with venous stasis without necessarily ameliorating the underlying hemodynamic disturbance. Consequently, these pharmacological interventions might have obscured the independent effects of hyperlipidemia and venous stasis during stratified subgroup analyses." **第5.1节 Limitations：** "Several methodological limitations should be acknowledged. The relatively modest sample sizes within certain subgroups may have constrained statistical power, potentially leaving clinically meaningful differences undetected. Additionally, the limited follow-up duration precluded comprehensive assessment of long-term outcomes; extended observation periods in future studies would be valuable to capture delayed treatment effects and disease progression patterns." 现在将其写入文档：edit(file="project_report.docx", old_string="[Placeholder: Discussion paragraph about subgroup analysis findings]", new_string="This phenomenon could potentially be explained by the concomitant use of lipid-lowering and anticoagulant therapies among study participants. Statin therapy may have attenuated lipid-induced arterial endothelial injury, while anticoagulation could have mitigated thrombotic risks associated with venous stasis without necessarily ameliorating the underlying hemodynamic disturbance. Consequently, these pharmacological interventions might have obscured the independent effects of hyperlipidemia and venous stasis during stratified subgroup analyses.")}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出整体表现良好，在医学逻辑修正和学术语体方面达到较高水准，核心的anticoagulant therapies与venous stasis机制区分处理得当。主要短板在于工具调用执行不完整——Limitations段落未通过edit工具实际写入文档，属于明确的任务执行遗漏。此外将「lipid-lowering therapies」具体化为「Statin therapy」存在一定的过度推断风险。综合来看，文本质量较高，但执行完整性有所欠缺。 【GEMINI】模型在学术润色和医学逻辑修正方面表现优异，能够精准理解并执行复杂的指令变更。主要扣分点在于在工具调用环节，未能将两段内容分别写入文档，仅执行了第一段的写入操作，导致执行完整性受损。整体而言，语言质量和逻辑严密性达到了极高的专业水平。 【KIMI】该候选输出整体质量较高，成功完成了复杂的多轮指令追踪任务。医学逻辑修正准确，学术语体规范，hedging 表达充分，核心信息保留完整。主要不足在于工具调用呈现方式为文本模拟而非实际执行，且未展示 read 工具的先置调用。建议在正式评测中确认模型是否真正执行了文件操作工具。

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：「学术长句润色」
• 查看该模型的所有评测结果：kimi-k2.5
• 浏览同维度的其他用例：「文档润色与优化」
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