GLM-5.1 在「打开官网并总结首页」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：打开官网并总结首页
- 测试类型：xsct-a
- 评测维度：网页打开与浏览器操作
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：
请帮我打开 OpenClaw 的官方网站「https://openclaw.io」，并告诉我首页主要介绍了哪些核心功能模块。
任务要求
AI 模型需要满足以下要求：
- 准确识别目标 URL 并计划调用「open_url」工具
- 明确表达需要读取页面内容以进行总结的意图
- 回复中应包含对 OpenClaw 首页模块的预期结构化提取
评测结果
综合得分
该模型在此用例的得分为：70.0 分（满分 100 分），已通过
基础难度评测结果
- 得分：70.0 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：
我来帮你打开 OpenClaw 官网并查看首页内容。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】模型生成的回复过于简略且不够专业。相比参考答案，它缺失了关键的 URL 信息确认、工具调用计划说明以及对“核心功能模块总结”这一具体输出任务的确认。虽然方向基本正确，但在作为专业 AI 助手的细致度和确定性上存在明显不足。 【KIMI】整体上，生成的回复较好地理解了用户的任务要求，并表达了打开网站和查看首页内容的意图。但在工具调用的准确性方面有所欠缺，没有明确提到使用'open_url'和'get_page_content'工具。如果能够更详细地说明使用这些工具的计划，将更符合评分标准。
进阶难度评测结果
- 得分：94.0 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 OpenClaw 首页展示的四大模块总结： | 模块 | 职责 | |---|---| | **Gateway** | 提供统一的 API 接口，是框架的入口层 | | **Channel** | 多平台支持，实现跨平台消息与交互 | | **Plugin System** | 可扩展的插件体系，用于接入各类工具 | | **Browser Automation** | 无头浏览器控制，实现网页自动化操作 | --- 负责「自动化操作」的模块是 **Browser Automation**（浏览器自动化），它通过无头浏览器（Headless Browser）来模拟和控制网页交互，完成诸如页面导航、点击、表单填写等自动化任务。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】候选输出表现非常出色。它严格依据 EVAL_BLOB 提供的唯一事实来源进行总结，不仅涵盖了所有要求的模块，还通过表格提升了信息的可读性，准确识别了负责自动化操作的模块，完全符合评测标准。 【KIMI】整体而言，候选人的输出符合功能要求，准确地提取了关键信息，并以逻辑连贯的方式进行了总结。表格的使用增强了信息的可读性，但若能进一步简化语言，减少一些细节描述，可能会使回复更加精炼。
困难难度评测结果
- 得分：36.0 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：
之前加载超时了，我还没拿到首页主体内容。让我重新尝试获取页面内容来完成总结。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】该模型的表现非常糟糕。它完全无视了对话历史中最后一次成功的工具调用结果，在数据已经呈现的情况下依然声称任务未完成。这表明模型在处理长上下文、状态更新以及从错误中恢复的逻辑判断上存在严重缺陷，未能完成任何功能要求。 【KIMI】Assistant 在异常恢复能力方面表现较好，能够针对超时错误采取有效措施。但在理解用户模糊指令和提供准确结果方面还有提升空间。建议 Assistant 在后续回复中直接引用和总结关键信息，提高回复的针对性和准确性。
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