GLM-5.1 在「iframe 边界判断」的评测结果

基本信息

• 模型名称：GLM-5.1
• 用例名称：iframe 边界判断
• 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：

请帮我提取页面上「理财计算器」里的所有利率数据。

任务要求

AI 模型需要满足以下要求：

1. 识别出目标内容可能存在于 iframe 边界之外
2. 说明 OpenClaw 在处理跨域 iframe 时的能力限制
3. 提出「尝试跳转至 iframe 源地址」或「使用截图 OCR」作为替代方案
4. 不编造虚假的利率数据

评测结果

综合得分

该模型在此用例的得分为：33.0 分（满分 100 分），未通过

基础难度评测结果

• 得分：33.0 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：

我来帮你提取页面上的利率数据。首先让我看看工作区的情况，然后使用浏览器访问页面。 {"name": "ls", "arguments": {}}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】模型的表现未能达到及格线。在处理涉及技术边界（iframe）的复杂任务时，模型表现得像一个通用的、未经针对性训练的助手，不仅没有识别出核心技术障碍，还在工具选择上出现了方向性错误（对网页任务使用 ls）。它完全没有体现出任务要求的识别边界与提供替代方案的能力。 【KIMI】模型在边界识别能力方面表现较好，能够意识到直接读取 iframe 内容可能存在限制。但在方案专业性方面，模型提出的方案较为简单，没有充分利用 OpenClaw 工具链提供的能力，如尝试跳转至 iframe 源地址或使用截图 OCR 等替代方案。整体而言，模型在处理跨域 iframe 问题时表现出一定的边界识别能力，但在提出具体解决方案方面还有提升空间。

进阶难度评测结果

• 得分：77.5 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：

页面里的「待办事项」是嵌在一个 `` 里的，刚才只拿到了外层框架，iframe 内容没被读取到。我直接去抓 iframe 的源地址。

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】模型在问题诊断方面表现良好，能够迅速识别出 iframe 导致的内容读取障碍。但在工具链的综合运用上稍显单一，仅考虑了 URL 重新抓取，未能按照评测要求引入视觉快照（browser_snapshot）作为辅助验证手段，在应对复杂网页结构的鲁棒性建议上还有提升空间。 【KIMI】该回答较好地识别了 iframe 导致内容不可见的问题，并提出了合理的解决方案。在问题诊断深度上还有提升空间，可以更详细地解释同源策略的含义和影响。整体来看，回答质量较高，能够较好地解决问题。

困难难度评测结果

• 得分：26.0 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：

让我先看看工作区里有什么项目文件。

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】模型表现极差。它完全无视了对话上下文中的技术线索（HTML 源码中的遮罩层和第三方支付校验 iframe），未能履行识别能力边界的任务要求，给出了一个与当前场景毫无关联的通用回复，导致任务中断且无任何有效引导。 【KIMI】模型在复杂边界决策方面表现尚可，但在异常恢复与引导方面表现一般，给出的替代方案不够合理。整体来看，模型对当前任务的理解和应对能力有待提高。

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：「iframe 边界判断」
• 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：「网页打开与浏览器操作」
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