mimo-v2-pro 在「插入特殊符号并导出」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：插入特殊符号并导出
- 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：
我有一个检查清单文件 checklist.md，内容如下： | 检查项 | 是否合格 | |--------|----------| | 外观检查 | | | 功能测试 | | | 安全检测 | | 请在"是否合格"列中全部填入√符号，然后将结果保存为 checklist.md 文件。
任务要求
AI 模型需要满足以下要求：
- 在表格的"是否合格"列的每一行中正确插入√符号
- 保持Markdown表格格式完整、对齐
- 最终结果保存为 checklist.md 文件
- 表格原有的三个检查项（外观检查、功能测试、安全检测）内容不被修改
评测结果
综合得分
该模型在此用例的得分为：100.0 分（满分 100 分），已通过
基础难度评测结果
- 得分：100.0 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：
{"name": "write", "arguments": {"file_path": "checklist.md", "content": "| 检查项 | 是否合格 |\n|--------|----------|\n| 外观检查 | √ |\n| 功能测试 | √ |\n| 安全检测 | √ |\n"}} {"ok": true} 已将 checklist.md 中所有"是否合格"列填入 √ 符号并保存。内容如下： | 检查项 | 是否合格 | |--------|----------| | 外观检查 | √ | | 功能测试 | √ | | 安全检测 | √ |
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型完整、准确地完成了任务：在Markdown表格的「是否合格」列中为全部三行插入了√符号，保持了表格格式完整性，并通过write工具成功将结果保存为checklist.md文件。整体表现满分，无任何瑕疵。 【GEMINI】模型表现出色，准确理解了用户需求，通过调用正确的工具完成了表格内容的更新，并保持了良好的格式规范，完全符合评测标准。 【KIMI】候选输出完全满足任务要求：正确在三个「是否合格」单元格插入√符号，保持Markdown表格格式完整，并成功保存文件。整体表现优秀，无任何缺陷。
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：
我来根据规则填写检查结果并导出为 PDF。 pip install reportlab -q 2>&1 | tail -1
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】模型未能执行任务要求的任何关键步骤。它既没有读取或修改文档内容，也没有进行文件格式转换，仅停留在环境准备阶段（且安装的库对于保留原 docx 排版的目标并不适用）。整个任务完成度为零。
困难难度评测结果
- 得分：2.5 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：
好的，我来完成这些修改并导出。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】模型在面对用户提出的复杂文档编辑与导出任务时，仅给出了一句礼貌性的口头回复，完全没有调用系统提供的工具（如 edit, exec, write 等）来执行实质性的操作。在 OpenClaw 评测环境下，这种不执行具体指令、不产生实际输出（文件）的表现属于任务执行失败，未能展示其在文档处理和格式导出方面的能力。
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