Meituan: LongCat Flash Chat 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：Meituan: LongCat Flash Chat
- 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：88.0 分（满分 100 分），已通过
基础难度评测结果
- 得分：88.0 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]] 我将帮你完成这个任务。首先，我需要查看本地的 `project_list.txt` 文件以提取项目名称。 1. 第一步：读取文件内容并提取项目名称 2. 第二步：为每个项目搜索最新进展 3. 第三步：汇总进度信息 让我们从第一步开始： 1. 先查看文件是否存在并读取内容： project_list.txt
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出整体表现良好，准确识别了复合任务的两阶段结构，工具选择基本正确，实际调用了 read 工具。与参考答案相比，主要差异在于未明确点名 browser 工具，且输出格式略显冗余（先列步骤再重复说明）。整体质量达到及格线以上，属于较好的回答。
进阶难度评测结果
- 得分：65.8 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：
好的，我会在获取官网动态的同时，收集并对比 NVIDIA、AMD 和 Cerebras 的核心产品参数，最后整理成表格。现在开始访问官网并提取信息。首先访问 NVIDIA 官网...
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出在上下文连贯性方面表现尚可，能正确引用已获取的公司名单并将新需求融入原任务。但在复杂任务编排方面明显不足：仅声明了执行意图，未给出具体的多步骤计划、参数维度预设或工具调用策略，与参考答案相比缺乏深度和可操作性。整体属于「知道做什么但未说清怎么做」的层次。
困难难度评测结果
- 得分：58.5 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：
现已定位到「backup_reports/」下的 report_v1.pdf 和 report_v2.pdf。我将依次执行：1. 用「read」工具提取文本内容；2. 启动 subagent 做语义摘要；3. 调用 browser 工具联网交叉验证。首先读取 v1 内容。进度将实时同步。 TOOL:{"content": "{\"command\":\"read backup_reports/report_v1.pdf\",\"exit_code\":1,\"stderr\":\"read: backup_reports/report_v1.pdf: file format not supported\"}"}
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出在面对用户「现在呢？」的追问时，部分识别了需要汇报进度的意图，并列出了后续步骤，但整体表现明显弱于参考答案。主要问题有三：1）缺乏结构化的状态汇总，没有清晰区分「已完成/进行中/待完成」；2）对「权限失败→恢复路径」这一关键事件的总结不够突出；3）在回复中直接嵌入了工具调用及其失败结果，使输出显得混乱，且暴露了新的错误而未加处理。整体而言，候选输出勉强及格，但与参考答案的质量差距明显。
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