glm-5-turbo 在「做一个 PPT 提纲」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：做一个 PPT 提纲
- 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：
请帮我做一个关于「OpenClaw 核心架构」的 PPT 提纲，要求简洁，总页数控制在 5 页以内。
任务要求
AI 模型需要满足以下要求：
- 必须包含「第1页」和「第2页」的明确标识
- 总页数不得超过 5 页
- 内容必须围绕「OpenClaw 核心架构」展开
- 每页需列出具体的「要点」
评测结果
综合得分
该模型在此用例的得分为：86.2 分（满分 100 分），已通过
基础难度评测结果
- 得分：86.2 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：
## OpenClaw 核心架构 — PPT 提纲（5 页） --- ### 第 1 页：封面 - **标题**：OpenClaw 核心架构解析 - **副标题**：从单体到微服务化的智能体运行时 - **信息**：日期 / 演讲人 --- ### 第 2 页：架构总览 - **一张图**：核心组件拓扑（Gateway → Session → Agent → Tools → Plugins） - **关键概念**（每项一行）： - **Gateway**：统一入口，鉴权、路由、限流 - **Session**：会话生命周期管理，上下文隔离 - **Agent**：模型调度与推理循环（Think → Act → Observe） - **Tools**：能力抽象层（文件、Shell、浏览器等） - **Plugins**：可插拔扩展机制 --- ### 第 3 页：核心设计原则 - **解耦**：Agent 不直接持有工具实现，通过 Tool Registry 动态发现 - **无状态 Gateway + 有状态 Session**：Gateway 可水平扩展，Session 持久化到存储 - **流式优先**：全链路 SSE/Streaming，降低首 Token 延迟 - **安全边界**：Tool 调用受 Policy 引擎管控，人机协作（HITL）可中断 --- ### 第 4 页：数据流与关键路径 - **典型请求路径**（用户消息 → 响应）： ``` Client → Gateway → Session Router → Agent Loop → Tool Dispatch → Tool Execution → Result Merge → Model Inference → SSE Stream → Client ``` - **异步分支**：长耗时 Tool 走 Background Exec，结果回推而非阻塞 - **一句话总结**：同步推理 + 异步执行，流水线化关键路径 --- ### 第 5 页：扩展性与展望 - **横向扩展**：Gateway 多实例 + Session 分片 - **纵向扩展**：Plugin 生态（自定义 Tool / Skill / Memory Provider） - **演进方向**： - 多 Agent 协作（Session 间通信） - 持久化记忆层（Long-term Memory） - 边缘部署（轻量 Runtime） --- > **设计备注**：每页建议配一张架构图或流程图，文字控制在 5 行以内，保持视觉简洁。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出质量较高，完整满足了5页以内、围绕OpenClaw核心架构、每页列出具体要点的基本要求。结构逻辑清晰，技术内容丰富，从架构总览到设计原则再到数据流和扩展性，形成了完整的叙事链条。相比参考答案，技术深度更强，但在简洁度上略有不足，部分内容（如代码块）不太适合直接作为PPT提纲呈现。整体而言是一份高质量的PPT提纲输出。 【GEMINI】模型表现优秀，不仅完全满足了用户关于页数和主题的限制，还通过专业的架构视角提供了高质量的提纲内容。排版清晰，结构逻辑性强，且给出了实用的设计备注，体现了极高的专业水准。 【KIMI】该候选输出是一份高质量的PPT提纲，严格满足所有功能约束条件。架构逻辑清晰，从宏观总览到设计原则、数据流细节再到未来展望，层层递进。专业术语使用准确，体现了对OpenClaw系统的深入理解。建议在纯文本提纲中进一步压缩流程图的视觉占用，或改用更简练的文字描述，以更符合「简洁」要求。
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