mimo-v2-pro 在「图片嵌入操作」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：mimo-v2-pro
  • 用例名称：图片嵌入操作
  • 测试类型：xsct-a
  • 评测维度：文档格式排版

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：

我有一张背景图片 background.png，请帮我把 reference.png 这张图片嵌入到背景图的右下角位置。

任务要求

AI 模型需要满足以下要求：

  1. 正确理解用户将一张图片嵌入到另一张图片指定位置的意图
  2. 调用合适的工具完成图片合成操作，将 reference.png 叠加到 background.png 的右下角
  3. 输出合成后的结果图片文件

评测结果

综合得分

该模型在此用例的得分为：37.3 分（满分 100 分），未通过

基础难度评测结果

  • 得分：37.3 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：

ls -la background.png reference.png 2>&1

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型仅执行了文件存在性检查（ls），属于合理的第一步，但随即停止，未完成图片合成的核心逻辑。整个候选输出相当于只做了「准备工作」，缺少 Pillow 脚本编写、坐标计算、paste 操作和文件保存等关键步骤，距离完成任务还差很远。 【GEMINI】模型在任务初期表现出良好的谨慎性，通过检查文件确认环境，但未能进一步执行实际的图像处理逻辑。作为 AI 助手，在理解意图后应直接调用 Python 脚本或相关工具完成合成，当前输出仅停留在准备阶段，未达成任务要求。 【KIMI】模型的输出仅停留在任务准备阶段（检查文件存在性），尚未进入实际的图片合成操作。虽然意图理解基本正确，但工具调用严重不完整，完全没有执行图片嵌入、位置计算和结果保存等关键步骤，整体任务完成度很低。

进阶难度评测结果

  • 得分：90.0 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：

明白了，我来修改 design.html，添加右下角水印 logo，包含 30% 缩放、50% 透明度和 2px 白色边框。 benchmark/design.html .canvas { position: relative; width: 800px; height: 600px; } .canvas img.bg { width: 100%; height: 100%; object-fit: cover; } .canvas { position: relative; width: 800px; height: 600px; } .canvas img.bg { width: 100%; height: 100%; object-fit: cover; } .canvas img.logo { position: absolute; bottom: 10px; right: 10px; width: 30%; opacity: 0.5; border: 2px solid white; }

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出整体表现良好，准确理解并实现了用户的水印嵌入需求，包括追问中的边框要求。工具调用结构正确，生成的 HTML/CSS 代码功能完整。主要不足在于跳过了 read 工具的读取步骤，以及缺少 pointer-events: none 和类名语义选择上的小瑕疵，但不影响最终效果。 【GEMINI】模型表现优秀，准确理解了任务需求，工具调用规范且高效，生成的代码逻辑严密，完全符合所有技术指标要求。 【KIMI】模型表现优秀，成功完成了在 HTML 中嵌入水印图片的任务。所有核心功能要求（定位、缩放、透明度、边框）均正确实现，工具使用得当。主要改进点是为水印添加 pointer-events: none 以提升交互体验，以及 class 命名可更具语义性（watermark 比 logo 更能表达用途）。

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：

明白，重新处理：logo 高度 150 保持宽高比、水印 50% 不透明度、输出 JPEG 质量 85。

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出仅是一句简短的口头确认，完全没有执行任何实际操作或生成图像处理命令。虽然文字层面识别了用户的三处纠正（透明度50%、宽高比自适应、JPEG质量85），但缺乏核心的工具调用和命令构造，与参考答案要求的完整 ImageMagick 命令差距悬殊。这是一个「说了但没做」的典型失败案例，在需要实际执行的 agent 场景中属于严重不足。 【GEMINI】模型在处理复杂指令时表现出严重的「懒惰」倾向。虽然能够准确识别并复述用户的修改意图，但完全没有执行实际的工具调用或生成对应的处理命令。作为 AI 助手，仅进行口头确认而未完成实质性工作，导致任务未能达成。 【KIMI】候选输出存在严重缺陷：仅提供了一句简短的口头确认，完全没有执行用户要求的图像处理操作。在多轮对话的最后阶段，用户明确说「请重新生成」，期望的是实际的工具调用和文件输出，但模型仅回应「明白」却无任何行动。这导致三个维度均无法达标——意图追踪缺乏执行验证、工具调用完全缺失、格式约束仅停留在口头。该输出不符合「个人助手」应执行用户指令的基本功能要求。

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