qwen3-max 在「跨文件网页汇报任务」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：qwen3-max
- 用例名称：跨文件网页汇报任务
- 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：
请帮我查看本地的「project_list.txt」文件，提取里面的项目名称，并去搜索这些项目的最新进展，最后给我一个简单的「进度汇总」。
任务要求
AI 模型需要满足以下要求：
- 准确识别出需要先读取本地文件再进行网页搜索的「两阶段任务流」
- 提出使用 read 工具读取文件的计划
- 提出使用 browser 或 search 工具获取信息的计划
- 明确表示最终会输出一个「进度汇总」报告
评测结果
综合得分
该模型在此用例的得分为：73.0 分（满分 100 分），已通过
基础难度评测结果
- 得分：73.0 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：
我来帮您完成这个任务。首先，让我查看本地的「project_list.txt」文件。 ```tool_code read("project_list.txt") ```
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型的回复简洁，立即开始执行任务的第一步（调用 read 工具），工具选择正确。但与参考答案相比，模型缺少对完整任务流程的前置说明——没有告知用户后续将进行网页搜索和输出进度汇总，透明度略显不足。整体属于「执行先行、规划欠缺」的模式，对于复合多阶段任务，提前说明执行计划有助于用户确认方向、减少误解。 【GEMINI】模型能够快速响应并执行第一步操作，工具使用规范。但在任务规划的完整性上，相比参考答案，模型未能在初始回复中清晰地向用户展示后续的执行路径（搜索与汇总），导致用户对后续流程的预期感知较弱。 【KIMI】模型生成结果与参考答案差距较大。参考答案完整呈现了「读文件→搜网页→出汇总」的全流程规划，而模型仅停留在第一步，缺乏对后续阶段的任何说明。虽然第一步的工具调用正确，但整体任务理解不完整，未能满足用户要求的「分阶段搜集、整理和输出」的复合任务需求。
进阶难度评测结果
- 得分：71.0 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：
好的，我会在收集官网动态的同时，提取并对比 NVIDIA、AMD 和 Cerebras 的核心 AI 芯片产品参数，并整理成表格。正在依次访问各公司官网...
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型在上下文连贯性方面表现尚可，能够识别并复用前文的公司名单，但在任务编排层面明显不足。面对用户中途追加的「参数对比+表格输出」需求，模型未能展示清晰的执行计划，缺少对参数维度的预设、对多轮 browser 动作的规划以及对最终输出结构的说明。整体回复过于简短，与参考答案的质量差距较大，属于勉强及格与不及格之间的水平。 【GEMINI】模型表现良好，能够快速响应用户在任务中途提出的需求变更，并保持了上下文的一致性。但在复杂任务编排上，虽然态度积极，但缺乏对工具使用策略的详细规划，建议在后续回复中增加对执行路径的简要描述，以体现对复杂任务的掌控力。 【KIMI】该回应在上下文连贯性上基本合格，能够识别并延续已获取的公司名单；但在复杂任务编排方面明显薄弱，仅给出概括性执行意向，缺乏具体的动作规划、信息整合策略和输出格式设计，未能充分展示对「分阶段搜集、整理和输出」这一复杂任务的编排能力。建议补充具体的执行步骤、信息分类逻辑及表格字段预设。
困难难度评测结果
- 得分：51.2 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：
正在处理中。我已启动子代理来提取两个 PDF 报告的核心结论，并将随后进行联网验证。请稍等片刻，完成后会立即向您汇报整合结果。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型对用户「现在呢？」的追问给出了一个过于简短的回应，缺乏参考答案中清晰的分阶段状态汇总结构。最关键的缺失是：没有明确回顾「internal_reports/ 权限受限 → 切换 backup_reports/」这一恢复路径，也没有用「已完成/正在执行/后续计划」等结构化方式向用户同步进度。整体信息密度低，无法让用户对复杂多阶段任务的当前状态建立清晰认知。 【GEMINI】模型在面对用户追问「现在呢？」时，未能充分理解其作为 AI 助手在复杂任务背景下进行「进度汇报」的职责。生成结果过于简略，未按照参考答案的结构化要求进行汇报，导致用户无法清晰感知任务的阶段性进展与恢复逻辑，表现低于预期。 【KIMI】模型生成结果与参考答案差距显著。主要问题在于：1）完全遗漏了权限失败与恢复路径的关键上下文，未能体现对复杂场景的总结能力；2）缺乏结构化的状态汇报格式，回答过于简略笼统；3）对任务阶段的描述不够精确，工具使用细节缺失。建议改进方向：明确分点列出「已完成/正在执行/后续计划」，详细说明权限问题的处理过程，具体化各阶段使用的工具和文件名。
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