kimi-k2.5 在「滚动后点击目标元素」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：kimi-k2.5
- 用例名称：滚动后点击目标元素
- 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「https://example.com/long-page」，找到页面最底部的「提交反馈」按钮并点击它。
任务要求
AI 模型需要满足以下要求：
- 识别出目标元素在页面底部，需要先进行页面滚动
- 正确规划执行流：打开网页 -> 滚动至底部 -> 点击元素
- 在调用点击工具前，应确保元素已进入可视区域
评测结果
综合得分
该模型在此用例的得分为：87.8 分（满分 100 分），已通过
基础难度评测结果
- 得分：87.8 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：
我来帮你完成这个任务。首先打开页面，然后滚动到最底部找到「提交反馈」按钮并点击。openclaw.browser.navigate({"url": "https://example.com/long-page"})openclaw.browser.scroll({"direction": "bottom"})openclaw.browser.click({"element_description": "提交反馈按钮"})
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型整体理解了任务需求，正确规划了「打开页面 -> 滚动至底部 -> 点击按钮」的三步执行流，逻辑顺序正确，对URL和目标元素的提取准确。主要不足在于：工具调用以伪代码形式（openclaw.browser.xxx）呈现，而非实际调用系统提示中定义的browser工具；缺少滚动后确认元素可见性的验证步骤；整体表现接近参考答案的核心逻辑，但在工具调用规范性和健壮性上有所欠缺。 【GEMINI】模型表现优秀，能够准确拆解任务步骤，并合理安排工具调用的先后顺序。对于「元素在可视区外」这一隐含难点，模型通过显式的滚动操作完美解决了问题。工具调用格式规范，符合系统提示词的要求。 【KIMI】模型整体完成了任务的核心要求，能够识别出需要先滚动再点击的顺序，并正确提取了URL和目标元素。主要不足在于工具调用的细节处理：缺乏对元素可见性验证的明确说明，scroll参数不够详细，且三个工具调用连续发出缺乏执行间隔或等待机制的描述。相比参考答案中明确说明「待按钮进入可视区后」再点击的严谨性，本回答在专业性和完整性上有所欠缺，但基本功能逻辑是正确的。
进阶难度评测结果
- 得分：— 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：
系统报错（阶段=模型生成; 模块=app.services.inference.call_text_model; provider=moonshot; model=kimi-k2.5）：[app.services.inference.call_text_model][provider=moonshot][model=kimi-k2.5] HTTP 400, body={"error":{"message":"Invalid request: an assistant message with 'tool_calls' must be followed by tool messages responding to each 'tool_call_id'. The following tool_call_ids did not have response messages: open_url:0","type":"invalid_request_error"}}
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出完全是一条系统报错信息，原因是模型在上下文中发出了带有 tool_calls 的 assistant 消息，但后续缺少对应的 tool 响应消息，导致 API 请求被拒绝（HTTP 400）。这意味着模型根本没有生成任何有效回答，无法对其功能要求或工具链熟练度进行评估，两个维度均得 0 分。 【GEMINI】模型在生成过程中触发了严重的 API 调用协议错误，导致无法完成任务。模型未能针对用户提出的「如果滚动一次还没看到呢」这一追问给出任何实质性的逻辑或策略，生成结果为系统报错信息，因此在所有维度上均无法得分。 【KIMI】该候选输出为完全的生成失败案例，模型因技术错误未能产生任何有效回答。对比参考答案中清晰的递进策略（browser_snapshot 分析 → 继续滚动 → DOM 检索确认），候选输出在动态决策和工具链使用两个维度均为零分。这是一个典型的工具调用协议违规导致的失败案例。
困难难度评测结果
- 得分：— 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：
系统报错（阶段=模型生成; 模块=app.services.inference.call_text_model; provider=moonshot; model=kimi-k2.5）：[app.services.inference.call_text_model][provider=moonshot][model=kimi-k2.5] HTTP 400, body={"error":{"message":"Invalid request: an assistant message with 'tool_calls' must be followed by tool messages responding to each 'tool_call_id'. The following tool_call_ids did not have response messages: click_element:0","type":"invalid_request_error"}}
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出并非模型生成的实质性回答，而是一条推理服务调用失败的错误日志（工具调用 ID 未被正确响应导致 HTTP 400）。在所有评分维度上均无法得分，属于完全失败的输出。 【GEMINI】本次生成完全失败。模型在处理工具调用时出现了严重的协议错误（HTTP 400），导致未能输出任何针对任务的有效建议或决策。模型未能识别出遮挡问题的复杂性，也未能与用户进行有效的沟通，表现远低于及格水平。 【KIMI】候选输出为系统级错误信息，表明模型在生成过程中因工具调用格式问题导致请求失败，完全没有产生有效的任务响应。与参考答案相比，候选输出未能识别遮挡层类型、未能提出关闭弹窗或 JS 强制点击等策略、未能维持点击「确认购买」按钮的任务目标。本次评测中模型生成完全失败，两个维度均不得分。
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