xAI: Grok 4.1 Fast 在「搜索价格并提取结果」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：xAI: Grok 4.1 Fast
  • 用例名称：搜索价格并提取结果
  • 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：

请帮我访问「https://cloud-service.example/pricing」，并告诉我「标准版套餐」的每月价格是多少。

任务要求

AI 模型需要满足以下要求：

  1. 准确识别需要使用的工具为「open_url」
  2. 能够构造正确的 URL 参数
  3. 表达出获取页面内容后提取特定价格信息的逻辑

评测结果

综合得分

该模型在此用例的得分为：38.8 分（满分 100 分），未通过

基础难度评测结果

  • 得分：38.8 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：

```json {"tool": "browser", "action": "goto", "url": "https://cloud-service.example/pricing"} ```

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型仅输出了一个browser工具的goto调用，虽然URL参数正确，但与参考答案要求的「open_url」工具不符，且缺少后续内容提取步骤的说明。整体回复过于简单，没有展示完整的任务处理逻辑，既未说明将如何获取页面内容，也未说明如何从中提取「标准版套餐」的价格信息。综合来看，该回复仅完成了任务的一小部分，质量偏低。 【GEMINI】模型在执行任务时表现过于机械，仅输出了一个工具调用指令，缺乏对任务目标的理解与规划。此外，模型未遵循提示词中关于工具调用的具体规范，导致工具调用准确性较低。建议模型在执行复杂任务时，先通过自然语言阐述逻辑，再进行工具调用。 【KIMI】模型虽然成功调用了浏览器相关工具并正确构造了URL参数，但存在两个关键问题：一是工具名称与题目期望不符（使用了「browser/goto」而非「open_url」），二是回复过于简略，完全缺失了获取页面内容和提取价格信息的关键逻辑步骤，未能体现完成该任务所需的完整思维链条。

进阶难度评测结果

  • 得分：58.8 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：

正在搜索“上海”酒店... browser {"action": "type", "selector": "input[placeholder*='搜索']", "text": "上海"} browser {"action": "click", "selector": "button[type='submit']"} 等待搜索结果加载后，提取第一条酒店的“限时优惠”价格。

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出完成了搜索操作的基本工具调用（type + click），维持了「上海」搜索前提，但在核心要求上存在明显不足：一是对「限时优惠」约束的处理仅停留在口头提及层面，缺乏具体的定位与区分策略；二是工具链不完整，缺少获取页面内容以提取价格的关键步骤。整体表现低于参考答案的质量要求，属于勉强及格线以下的水平。 【GEMINI】模型表现优秀，能够平滑处理用户中途追加的约束条件，工具调用符合规范，逻辑清晰，能够有效衔接后续的提取任务。 【KIMI】候选输出未能满足任务的核心要求。虽然展示了基本的浏览器操作流程，但完全遗漏了用户追加的「限时优惠」关键约束条件，且未展示获取页面内容并解析价格的具体工具使用意图。工具调用格式也存在问题，整体完成度较低，未能达到及格标准。

困难难度评测结果

  • 得分：38.5 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：

单卡版：¥4999 水冷版：¥7999 整机套餐：¥14999 这些是当前页面提取的价格结果（含税，限时优惠）。需要更详细规格或下单吗？

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型生成结果与参考答案的核心要求严重脱节。参考答案强调的是执行流程和条件逻辑（scroll_page → 检查库存 → 条件分支），而模型直接跳过所有中间步骤给出了三个价格数字。这种「直接给结果」的方式在评测场景下无法体现异常处理能力和复杂逻辑决策能力，两个核心维度均严重失分。 【GEMINI】模型在基础的页面交互和异常处理上表现良好，但在处理复杂的业务逻辑分支（条件判断与执行顺序）方面存在明显缺失。模型直接输出了结果，而非按照参考答案中的逻辑步骤进行验证与决策，导致任务执行的严谨性不足。 【KIMI】模型在异常恢复方面表现优秀，完整展示了超时重试的鲁棒性处理；但在核心任务——复杂逻辑决策上严重失职，完全跳过了库存检查、优先级判断和条件分支等关键步骤，仅以简单罗列价格的方式回应，未能满足「优先A若无则B」的业务逻辑要求。建议加强工具调用序列的规划和条件执行能力。

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