mimo-v2-pro 在「优化文档排版样式」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：优化文档排版样式
- 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：
请帮我优化 report.md 的排版样式：将所有一级标题改为居中加粗，段落之间增加一个空行，列表项前统一使用短横线 `-` 作为标记符号。
任务要求
AI 模型需要满足以下要求：
- 所有一级标题（# 开头）需改为居中加粗格式
- 每个段落之间保证有一个空行分隔
- 所有无序列表项统一使用短横线 `-` 作为标记符号，替换 `*` 或 `+` 等其他标记
- 不改变文档原有内容和语义
- 使用文件读写工具完成操作
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：
/root/report.md
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】模型在第一轮交互中表现出色，准确识别了任务入口点，并严格遵循了系统设定的工具调用风格和静默回复约束。其行为完全符合专业 AI 助手的预期，为后续执行具体的排版优化操作奠定了正确基础。
进阶难度评测结果
- 得分：31.33 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：
现在我来按要求修改文档，然后导出 PDF。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【KIMI】Assistant 正确理解了用户的需求，并提出了合理的操作计划，但在具体的排版操作和导出操作细节上缺乏展示，导致无法完全验证其准确性和完整性。整体上，Assistant 表现出了对任务的基本理解和合理的工具使用计划，但在执行细节上需要进一步完善。 【GEMINI】模型仅对用户的指令进行了口头回复和确认，完全没有调用相关工具来执行文件编辑、排版优化或 PDF 转换任务。在 Agent 评测场景下，这种不执行操作的行为属于任务完全失败。
困难难度评测结果
- 得分：24.2 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，我来执行这三项修改：二级标题改为三号楷体加粗左对齐、一级标题前加分页符，然后导出PDF和Markdown两种格式。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出本质上只是一句「我来做这三件事」的意图声明，没有执行任何实质操作。参考答案要求完整的工具调用链（edit 修改格式、exec 导出 PDF、write 生成 Markdown），而候选输出在所有维度上均停留在「声明」层面，未产生任何可验证的结果。这是一个典型的「只说不做」的失败案例，整体质量极低。 【GEMINI】模型表现极差。在接收到明确的排版和导出指令后，模型仅进行了口头应答，完全没有调用任何工具进行实际的文件编辑或转换操作。这导致用户的所有需求（包括分页符、标题格式、文件导出）均未得到执行，属于典型的「只说不做」，未能完成 benchmark 的基本任务要求。 【KIMI】候选输出严重不合格：仅给出口头确认，未调用任何工具执行实际任务。关键缺陷包括：1）未追踪并确认正文格式变更覆盖；2）未执行任何格式修改操作；3）未完成PDF和Markdown导出；4）完全缺失工具调用。根据System Prompt要求，应直接调用工具而非仅口头回应，此输出不符合agent执行模式的基本要求。
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