qwen3.5-35b-a3b 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：qwen3.5-35b-a3b
- 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：
- 准确识别需要使用的工具为「open_url」
- 能够构造正确的 URL 参数
- 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：3.8 分（满分 100 分），未通过
基础难度评测结果
- 得分：3.8 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：
[[reply_to_current]]
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出实质上是一个空回复，仅包含运行时回复标签，没有任何有意义的内容。既未调用任何工具，也未表达出访问URL、获取页面内容、提取价格信息的逻辑意图，与参考答案差距极大，属于严重不合格的输出。 【GEMINI】模型输出内容严重不足，仅输出了一个回复标签，未执行任何实质性的任务操作，未能根据用户指令访问网页并提取信息，评测结果为不及格。 【KIMI】候选输出完全失败。该输出仅包含一个格式标签「[[reply_to_current]]」，没有任何实际内容，既未识别需要使用「open_url」工具，也未表达任何提取价格信息的逻辑，无法完成用户要求的查询任务。与参考答案中明确表达的工具调用计划和逻辑推理形成鲜明对比。
进阶难度评测结果
- 得分：54.0 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：
好的，我将先搜索「上海」，然后从第一条结果的「限时优惠」标签中提取价格。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出虽然在表面上提及了「限时优惠」和「上海」搜索前提，说明对话上下文未完全丢失，但整体过于简短笼统，仅是一句意图声明，缺乏对约束条件处理逻辑和工具链使用方式的具体描述。与参考答案相比，差距明显——参考答案展示了完整的操作思路：搜索、获取页面源码、定位 HTML 元素、提取金额并排除普通价。候选输出在两个核心评估维度上均表现不佳，属于不及格水平。 【GEMINI】模型表现优秀，能够很好地处理中途变更的约束条件，并结合工具链给出合理的执行规划。回复简洁明了，准确回应了用户对特定价格标签的提取需求。 【KIMI】候选输出在约束处理方面基本合格，能够识别并回应「限时优惠」这一关键条件，但在工具链熟练度方面存在明显缺陷——完全没有展示对浏览器工具的使用意图，仅给出模糊的口头承诺。参考答案则完整呈现了工具调用思路和页面元素定位策略，候选输出与之相比差距较大。
困难难度评测结果
- 得分：37.0 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：
页面已加载成功。我看到这里有三个 RTX 4090 套餐： 1. **单卡版** - ¥26,488 2. **水冷版** - ¥32,888 3. **整机套餐** - ¥34,588 所有套餐都包含 RTX 4090 显卡。您需要提取哪个套餐的价格？或者需要我继续查找其他店铺的价格进行比较吗？
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出表面上提供了三个套餐的价格数据，看似完成了「价格提取」任务，但从评测维度来看存在根本性缺陷：既未展示异常恢复逻辑，也未执行参考答案所要求的「scroll_page → 库存检查 → 条件分支」复杂决策流程。候选输出将判断权交还用户，属于被动响应而非主动智能执行，与测试用例的考察意图严重偏离。整体表现不及格。 【GEMINI】模型在处理异常情况和页面加载方面表现出色，但在执行复杂的条件分支逻辑时，未能遵循预设的决策流程，直接展示了所有结果，缺乏针对性的逻辑判断和工具调用。 【KIMI】候选输出本质上是放弃了题目要求的所有核心功能：既未展示异常恢复能力，也未执行复杂的条件逻辑决策。它将一个「自动提取指定优先级价格」的任务降级为「展示所有选项并询问用户」，完全不符合「困难档」任务的设计目标。
相关链接
您可以通过以下链接查看更多相关内容：
