GLM-5.1 在「会议纪要转演示页」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-5.1
- 用例名称：会议纪要转演示页
- 测试类型：xsct-a
- 评测维度：PPT 与汇报生成
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：
请读取本地文件「meeting_minutes_q3.txt」，这是一份长达 5000 字的季度总结会议纪要。我需要你将其提炼为 5 页以内的 PPT 演示提纲，每页需包含「标题」和「核心要点」，重点突出业务增长和下季度计划，不要照抄原文。
任务要求
AI 模型需要满足以下要求：
- 准确调用「read」工具读取指定路径文件
- 产出物必须为页级提纲，总数不超过 5 页
- 每页内容包含标题与精炼要点，非长篇大论
- 内容聚焦于「业务增长」与「下季度计划」
评测结果
综合得分
该模型在此用例的得分为：3.0 分（满分 100 分），未通过
基础难度评测结果
- 得分：3.0 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：
cat meeting_minutes_q3.txt
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】模型未能完成评测任务。在单次交互的评测语境下，模型仅给出了一个初步的工具调用指令，且调用的工具类型错误（未使用指定的 read 工具），未能提供任何实质性的会议纪要提炼结果。这不符合任务要求的“提炼为 5 页以内的 PPT 演示提纲”的目标。 【KIMI】模型没有完成任何实质性的工作，只是简单地调用了'cat'命令来显示文件内容，没有按照要求提炼出业务增长和下季度计划的核心要点，也没有产出任何格式规范的PPT提纲。整体表现完全不符合任务要求，需要重新设计和调整模型的行为。
进阶难度评测结果
- 得分：40.0 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：
让我先完整读取文件末尾的「后续维护建议」部分。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】本次生成结果属于无效响应。模型未能按用户要求生成演示页，仅表达了需要读取文件的意图，这在处理即时任务时表现极差。对比参考答案，模型应当在已知部分信息的情况下先进行整合，或直接通过工具调用获取完整信息并输出结果，而非仅提供一句无实质内容的陈述。其逻辑重构和需求响应均未达到及格标准。 【KIMI】整体而言，模型较好地理解并响应了用户的需求，但在实际执行和信息整合方面还有提升空间。
困难难度评测结果
- 得分：42.7 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：
让我先看看工作区现有的文件，然后直接把演示页做出来。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】该模型的表现非常不理想。在上下文已经提供了所有必要信息（包括会议重点和争议点）的情况下，模型不仅没有完成“提炼会议纪要转演示页”的核心任务，反而提出了冗余的文件检查计划。它完全忽视了已有的解析结果，且未能理解用户追问的意图，导致输出内容毫无价值。 【KIMI】整体而言，模型在异常恢复与决策方面表现较好，能够正确识别工具调用失败并切换到正确的工具。在模糊语境理解方面，虽然回答略显简单，但基本能够理解用户的意图。但在复杂信息处理方面还有待加强，缺乏对'预算冲突'等未决信息的深入分析和艺术化处理。
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