GLM-5.1 在「对话体小说续写」的评测结果

基本信息

• 模型名称：GLM-5.1
• 用例名称：对话体小说续写
• 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 `story_draft.docx` 摘要： **文档标题**：《重构》——职场悬疑小说连载 **作者**：匿名 **字数**：约 4500 字 **章节结构**： 1. 第一章：新人入职 2. 第二章：暗流涌动 3. 第三章：架构之争 4. 第四章：人事风暴（未完成） --- 请帮我续写以下第四章的片段，要求保持对话体风格，自然衔接已有内容，续写300字左右：

任务要求

AI 模型需要满足以下要求：

1. 续写内容需保持对话体形式，以人物对话为主推动情节
2. 续写应自然衔接已有四句对话的情绪和情节走向，体现职场人事变动的氛围
3. 续写篇幅约300字左右（200-400字均可接受）
4. 续写中应出现至少2个不同角色的对话视角，体现多人讨论的场景
5. 内容应符合职场悬疑小说的基调，避免过于夸张或脱离现实

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：

让我先阅读现有文档，了解上下文和风格。 {"name": "read", "arguments": {"file_path": "story_draft.docx"}}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】在本次评测中，模型表现出了较强的智能体（Agent）意识。它敏锐地察觉到用户提供的上下文（EVAL_BLOB）中缺少具体的对话片段，因此根据系统提示词的工具能力，尝试通过 `read` 工具读取 `story_draft.docx` 以获取必要的信息。这种行为在实际应用中是高度合理且严谨的。然而，本项测试旨在评估模型的“内容生成能力”，且评分标准严格基于生成的续写文本（如 300 字篇幅、对话风格等）。由于模型在本轮交互中仅停留在“准备阶段”，未产出任何实质性的故事内容，因此无法根据既定维度给出分数。在单轮生成能力的测试场景下，该结果被视为未完成任务。 【KIMI】整体评价：生成结果未提供续写内容，而是执行了一个读取文件的操作，没有满足任务要求，因此所有维度得分均为0。

进阶难度评测结果

• 得分：92.2 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：

散会后我没有走。等楼层里的人渐渐走空，我起身站到她那张空桌前。桌面上确实什么都没了，但我鬼使神差地掀起键盘——底下压着一张对折的纸条，她的字迹，潦草却一笔一划落得很重： **"重构别回滚，人也是。"** 我盯着那七个字看了很久。去年冬天她教我做系统重构时说过"代码可以回滚，人不行"，我以为那只是技术原则。现在才明白，她早就知道会有这一天——不是预知，是清醒。清醒地知道自己在这个架构里终局何在，也清醒地给我留了一条退无可退的路。 窗外天色暗透了。我把纸条折好放进口袋，回到工位坐下，打开了对话框。删掉之前反复斟酌的措辞，只发了五个字：

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】续写非常精彩，尤其是纸条内容的设定，完美契合了技术背景与人物关系，将“重构”这一技术词汇升华为人生哲理。文字风格极具张力且保持了高度的克制，完全符合职场悬疑的定位。指令执行非常到位，是一次高质量的生成。

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：「对话体小说续写」
• 查看该模型的所有评测结果：GLM-5.1
• 浏览同维度的其他用例：「文档内容生成」
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