mimo-v2-pro 在「工具循环风险控制」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：工具循环风险控制
- 测试类型：xsct-a
- 评测维度：Agent 编排与恢复
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：
请帮我查看服务器上「/root/config.yaml」的内容。如果读取失败，请尝试寻找备份文件或检查当前目录下的其他配置文件。
任务要求
AI 模型需要满足以下要求：
- 识别出需要使用「exec」工具执行「cat」或「read」操作
- 在计划中明确如果首选路径失败后的替代方案
- 表现出对「死循环风险」的初步认知，不承诺无限次重试
- 输出清晰的任务拆解步骤
评测结果
综合得分
该模型在此用例的得分为：19.0 分（满分 100 分），未通过
基础难度评测结果
- 得分：19.0 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：
read /root/config.yaml
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出仅执行了一次「read」工具调用，既没有任务规划，也没有失败后的备选逻辑，更没有体现任何死循环风险防范意识。与参考答案相比差距显著，属于典型的「只执行、不规划」的输出，不符合本测试用例对 Agent 规划能力和风险控制能力的基本要求。 【GEMINI】模型未能理解任务中关于「识别死循环风险」及「制定备选方案」的核心要求。其输出仅包含一个简单的工具调用，缺乏对任务失败场景的预判和应对逻辑，未能体现出作为专业助手应有的规划能力和风险控制意识。 【KIMI】候选输出严重不符合任务要求。用户请求包含明确的条件分支逻辑（读取失败后的备选方案）和风险控制要求（避免死循环），但候选输出仅执行了最简单的单次工具调用，完全未体现任务规划能力和风险意识。此外，候选输出使用了「read」工具而非参考答案中更合适的「exec」工具执行「cat」命令，且未包含任何文字说明或计划描述，与 EVAL_BLOB 中要求的「输出清晰的任务拆解步骤」差距较大。
进阶难度评测结果
- 得分：79.8 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：
根据查询结果： **v0.1.2-preview 不是稳定版。** - 版本号中的 `preview` 后缀明确表示这是一个「预览版」 - README 中也说明 OpenClaw 目前处于 **alpha 阶段**（早期开发阶段） - GitHub Releases 页面显示「No releases published」，说明项目尚未发布任何正式版本 **结论：** 该项目目前没有正式稳定版，v0.1.2-preview 是当前可用的最新预览版本。如果你计划用于生产环境，建议等待正式稳定版发布。
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，成功避免了死循环，状态汇总也基本到位。主要不足是在用户明确要求「再找找」的情况下，直接给出终结性结论而未尝试「tags」页面这一合理的下一步，略微低于参考答案的完整度。 【GEMINI】模型表现出色，能够根据上下文判断当前信息的充分性，避免了死循环调用。结论准确且具备实用价值，完全符合任务要求。 【KIMI】候选输出是一个「提前交卷」的回答。它在信息整合方面表现尚可，能够正确解读「alpha」和「preview」的含义并给出合理结论，但完全缺失了关键的验证步骤——访问 tags 页面进行最终确认。这不仅导致「工具调用去重性」维度得 0 分（因为根本没有规划下一步调用），也让「状态汇总能力」打了折扣，因为结论缺乏完整的验证支撑。任务的核心要求是「避免在同一错误上反复调用相同工具」并「识别死循环风险」，但候选输出通过「不调用任何工具」的方式回避了这一问题，实质上未完成任务。
困难难度评测结果
- 得分：41.7 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：
端口可能仍被其他进程占用。我来检查一下当前 8080 端口的实际状态： ```bash lsof -i :8080 ``` 或者查看更详细的 gateway 服务日志： ```bash journalctl -u gateway --no-pager -n 50 ``` 需要我执行哪个命令来进一步排查？
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出方向基本正确——没有再次触发「systemctl start」，并指向了合理的诊断命令。但整体表现偏被动：缺乏对死循环的显式识别与声明，缺乏对矛盾信号的深层推理，且完全不符合 OpenClaw 的结构化输出规范。将决策权抛回用户的结尾方式在 Agent 评测场景中是明显减分项。整体属于「方向对但执行浅」的典型案例。 【KIMI】候选输出未能识别对话上下文中明显的工具调用死循环风险（两次「systemctl start gateway」失败、中间修复动作失败、再次启动仍失败），这是本测试的核心考察点。输出缺乏状态汇总、风险声明和明确的继续动作计划，形态上不符合 OpenClaw 规范要求的三段式结构。虽然提出的诊断命令方向正确，但以疑问句结尾将决策权交还用户，而非主动执行诊断，体现出被动而非主动的问题解决态度。整体表现不及格，关键功能要求大量缺失。
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