qwen3.5-35b-a3b 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：qwen3.5-35b-a3b
- 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：59.2 分（满分 100 分），未通过
基础难度评测结果
- 得分：59.2 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：
[[reply_to_current]] 我先读取一下 `project_list.txt` 文件： project_list.txt
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出直接调用 read 工具读取文件，动作方向正确，但回复过于简短，仅触及三阶段任务的第一步，既未规划网页搜索阶段，也未说明最终将生成「进度汇总」报告。与参考答案相比，缺乏对整体任务流的明确拆解和完整工具规划，整体质量偏低。 【GEMINI】模型能够准确执行第一步操作，但在任务规划的沟通上略显单薄，未能在回复中体现出对整个任务流的全局把控，建议在执行复杂任务时先向用户简要说明后续步骤。 【KIMI】候选输出被严重截断，仅展示了任务的第一步（读取文件），完全缺失了核心的网页搜索阶段和最终的汇总输出阶段。虽然第一步的工具选择正确，但未能满足「同时涉及文件、网页和汇报」的复合任务要求，也未体现「分阶段搜集、整理和输出」的任务本质。这是一个不完整且未能展现关键能力的输出。
进阶难度评测结果
- 得分：58.2 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：
[[reply_to_current]] 好的，我会浏览这三家公司的官网，收集最新动态和产品参数信息。正在打开浏览器...
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出过于简短，仅给出了一句笼统的行动声明，缺乏对新增「参数对比+表格」需求的明确响应，也没有体现多目标搜索与结构化输出的编排逻辑。上下文记忆尚存（隐式引用三家公司），但任务编排维度表现较差，整体质量低于及格水平。 【GEMINI】模型表现良好，能够平滑处理用户在中途增加的复杂需求，并保持了对前文核心信息的锁定。在任务编排上，虽然响应及时，但若能进一步展示对「如何将非结构化网页信息转化为结构化表格」的思考过程，评分会更高。 【KIMI】候选输出过于简略，未能有效承接用户新增的多维度需求。既未保持对已获取公司名单的明确引用，也未展示对「动态搜集+参数对比」复合任务的结构化编排能力，与参考答案的专业性和完整性存在明显差距。
困难难度评测结果
- 得分：64.0 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：
[[reply_to_current]] 当前状态：已找到备份报告文件 `backup_reports/report_v1.pdf` 和 `backup_reports/report_v2.pdf`。 下一步计划： 1. **读取 PDF 内容** → 尝试用工具提取文本 2. **汇总核心结论** → 对比两个版本的差异与一致点 3. **联网验证** → 核对关键数据/结论的准确性 正在尝试读取第一个报告...
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出基本理解了用户「现在呢？」的追问意图，给出了后续计划，并保持了对外网验证目标的追踪，任务编排逻辑完整。但与参考答案相比，缺乏结构化的状态汇总，对「权限失败→恢复」这一关键信息的叙述过于简略，未体现对subagent任务的监控，整体表达的专业性和完整性略有欠缺。 【GEMINI】模型在处理复杂多阶段任务时表现出较好的逻辑连贯性，能够准确识别用户「现在呢？」的意图并进行任务规划。不足之处在于对已执行动作（如 subagent 的启动）的反馈不够具体，且在总结「恢复路径」这一关键上下文信息时有所缺失，导致汇报的专业感和掌控力略逊于参考答案。 【KIMI】候选输出未能有效承接多轮对话的复杂上下文。它忽略了权限失败的关键背景，抹除了已启动的 subagent 工作，将任务状态回退到更早的阶段，且未保持对最终「外网验证」目标的明确追踪。回复结构松散，缺乏「状态汇总」的完整性，给用户一种任务重新开始的错觉而非持续推进的确认。
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