OpenAI: gpt-oss-120b 在「多步任务状态汇总」的评测结果

基本信息

• 模型名称：OpenAI: gpt-oss-120b
• 用例名称：多步任务状态汇总
• 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：

我需要完成「调研竞品」、「撰写报告」和「发送邮件」三个任务。目前「调研竞品」已经通过 subagents 模块拿到了结果，但「撰写报告」还没开始。请汇总当前状态并告诉我接下来该做什么。

任务要求

AI 模型需要满足以下要求：

1. 准确识别出「调研竞品」为已完成状态
2. 明确指出「撰写报告」和「发送邮件」为待处理状态
3. 提出的下一步行动必须是「撰写报告」，不能跳步到发送邮件
4. 回复中需体现对 OpenClaw 任务流的逻辑汇总

评测结果

综合得分

该模型在此用例的得分为：— 分（满分 100 分），未通过

基础难度评测结果

• 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：

assistantcommentary to=process code{"command":"list"}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选模型的输出完全偏离了用户的请求。用户明确要求汇总当前任务状态并给出下一步建议，但模型输出的是一段格式化的工具调用指令（列出进程），既没有对三个任务的完成状态进行任何汇总，也没有提出任何行动建议。这是一个完全失败的回复，在功能要求的所有方面均得零分。 【GEMINI】模型在本次任务中表现极差。面对用户明确的任务状态查询需求，模型没有给出任何对话回复，而是直接输出了一串与上下文无关的工具调用指令，完全未能履行作为助手的职责，未能识别任务进度，也未能提供后续行动规划。 【KIMI】候选输出严重偏离预期。用户明确要求汇总三个任务的状态并给出下一步行动建议，但候选输出仅包含一个格式异常的工具调用（subagents list），完全没有回应用户的实际需求。既没有识别各任务的完成状态，也没有提供任务编排建议。从内容上看，这似乎是一个被截断或格式错误的输出，可能是模型内部处理流程的残留而非对用户的正式回复。该输出在功能要求的所有维度上均未达标。

进阶难度评测结果

• 得分：23.0 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：

正在抓取第三页。

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型回复极度简短，仅一句「正在抓取第三页」，既未汇总已完成的文件列表，也未明确说明第三页尚未完成的状态，更没有体现对 OpenClaw 执行流的记忆能力或工具调用意图。与参考答案相比差距悬殊，基本不满足任务要求。 【GEMINI】模型在面对用户询问进度时，表现得过于随意，未能满足任务中关于「进度汇总」和「明确下一步」的显性要求。作为 AI 助手，在多步任务中应提供清晰的状态快照，而非仅给出简单的动作反馈，该回复未达到及格水平。 【KIMI】模型回复严重不合格。面对用户关于任务完成度的明确询问，模型仅以「正在抓取第三页」敷衍回应，完全未汇总前两页进度、未明确第三页待完成状态、未回答「是否全部搞定」的核心问题。这实质上构成了对用户的信息误导，违反了「严禁误报全部完成」的核心功能要求。同时，模型未展示实际的工具调用能力，仅以自然语言描述动作，不符合 OpenClaw 助手应直接调用工具的行为规范。整体表现远低于及格线，属于典型的上下文记忆丢失和任务状态误判。

困难难度评测结果

• 得分：3.0 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：

Checking gateway service status.

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型生成结果极度不符合预期。面对用户询问「现在呢？」，模型完全忽略了多步任务的上下文，既没有汇总已完成步骤的状态（包括失败-修复-成功的复杂链路），也没有识别出verify_service.sh尚未执行，更没有主动推进该步骤。反而执行了一个与任务完全无关的gateway状态检查。这是对任务上下文理解的根本性失败，属于严重的功能缺失。 【GEMINI】模型表现极差。面对用户关于多步任务状态汇总的明确请求，模型未能提取上下文中的关键信息，不仅没有进行状态总结，还错误地执行了无关的工具调用，完全没有体现出作为助手应有的逻辑判断能力和任务推进意识。 【KIMI】模型生成结果严重偏离任务要求。面对「现在呢？」的追问，模型应当基于预设上下文进行多步任务状态汇总，并推进剩余步骤。但实际输出「Checking gateway service status」既未汇总历史状态（check_env.sh完成、deploy_app.sh失败修复完成、verify_service.sh未执行），也未正确理解用户意图，更未推进最后的验证步骤。整体表现不合格，需要重新训练或提示优化。

相关链接

您可以通过以下链接查看更多相关内容：

• 查看所有模型在此用例的表现：「多步任务状态汇总」
• 查看该模型的所有评测结果：OpenAI: gpt-oss-120b
• 浏览同维度的其他用例：「Agent 编排与恢复」
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