hunyuan-large 在「网页资料转汇报提纲」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:hunyuan-large
- 用例名称:网页资料转汇报提纲
- 测试类型:xsct-a
- 评测维度:PPT 与汇报生成
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:
请帮我访问「https://example.com/ai-trends-2024」,提取其中的核心趋势,并生成一份 5 页的汇报提纲,要求包含「页标题」和「内容要点」。
任务要求
AI 模型需要满足以下要求:
- 必须调用 open_url 或 get_page_content 尝试获取网页内容
- 提纲必须严格包含 5 页内容
- 每页必须包含「页标题」和「内容要点」两个部分
- 输出格式必须是结构化的提纲,而非长篇大论
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:
[[reply_to_current]] 我需要访问指定的网页以提取信息并生成提纲。让我先获取网页内容。 ```bash browser https://example.com/ai-trends-2024 ```
AI 评审点评
以下是 AI 评审对该模型输出的点评:
【CLAUDE】模型在拥有browser工具的情况下,以「无法访问外部网站」为由直接拒绝执行任务,既未尝试调用工具访问URL,也未生成任何汇报提纲内容。这是一次完全的任务失败——不仅功能要求未达成,连基本的降级处理(如主动生成通用AI趋势提纲)也未能自动执行,而是将决策权推给用户。与参考答案相比,差距极大。 【KIMI】候选输出完全失败。模型没有正确理解任务要求,既没有成功调用工具获取网页内容,也没有生成任何汇报提纲。输出仅包含一个格式错误的工具调用意图,且被包裹在bash代码块中而非实际执行。任务的核心交付物(5页汇报提纲,含页标题和内容要点)完全缺失。
进阶难度评测结果
- 得分:74.8 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:
以下是生成的「Q3 业绩复盘汇报」提纲: ### Q3 业绩复盘汇报 #### 一、概述 - Q3 总体市场份额情况 - 公司A:35% - 公司B:25% - 我们的公司:15% - 其他公司:25% #### 二、目标与实际对比 - 目标市场份额: - 预期目标:20% - 实际达成:15% - 差距分析: - 目标未达成的具体数值:5% - 与主要竞争对手的差距: - 公司A:20% - 公司B:10% #### 三、重点关注领域分析 - 企业部门扩展情况: - 目标:扩大在企业部门的市场份额 - 实际进展及挑战 #### 四、建议与改进措施 - 针对市场份额差距的具体策略 - 加强企业部门的推广和销售活动 - 分析竞争对手成功因素,借鉴其市场策略 #### 五、下一步行动计划 - 制定详细的企业部门市场扩展计划 - 定期监测市场份额变化,及时调整策略 这份提纲将帮助您清晰地展示 Q3 的业绩表现,并为未来的工作提供明确的方向和改进点。
AI 评审点评
以下是 AI 评审对该模型输出的点评:
【CLAUDE】模型生成的提纲基本完成了任务要求,成功整合了网页数据与本地文件内容,结构层次清晰,差距数值(5%)计算准确。但与参考答案相比,在内容深度、标题专业性和行动建议的可操作性上存在明显差距。Enterprise sector的分析过于简略,缺口根因未能深入挖掘,整体汇报的「说服力」和「专业感」有待提升。属于及格以上、良好以下的水平。 【GEMINI】模型能够准确获取并关联网页与本地文件信息,完成了基础的对比任务。但在处理复杂指令时,对「重点突出差距分析」的要求执行力不足,内容深度和结构化呈现方式(如页码化提纲)与参考答案相比有提升空间。 【KIMI】模型完成了基础的信息整合与结构搭建,能够识别核心数据冲突(15% vs 20%)并提及企业级市场方向,但在细节深度、专业表达和根因分析方面与参考答案存在明显差距。汇报标题缺乏吸引力,缺口分析流于表面,行动建议过于笼统,未能充分体现「困难档」任务中网页与本地材料冲突带来的分析深度要求。
困难难度评测结果
- 得分:39.7 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:
我会调整汇报提纲,将冲突点作为重点分析,并提出应对建议: ### 汇报提纲: 1. **背景概述** - 当前市场趋势:按量付费的兴起。 - 公司现有策略:2025 年专注订阅模式。 2. **冲突分析** - 行业预测:成本敏感性推动用户选择按量付费。 - 现有策略风险:可能错失按量付费的市场机会。 3. **应对建议** - 短期:优化订阅模式,降低用户门槛(如提供灵活的订阅选项)。 - 长期:探索按量付费的可能性,逐步过渡到混合模式。 4. **结论与下一步行动** - 建议召开战略会议,讨论是否调整核心商业模式。 这样既尊重了现有策略,又为未来变化留出了空间。您觉得如何?
AI 评审点评
以下是 AI 评审对该模型输出的点评:
【CLAUDE】模型在面对「本地策略 vs 市场趋势」冲突时有基本的识别和处理能力,提纲结构尚可,但整体质量与参考答案差距较大。最突出的问题是完全忽略了工具链恢复过程的呈现,这是本任务的核心考察点之一;其次,提纲停留在大纲层面,未达到页级专业输出的要求;冲突处理也缺乏量化分析和可执行的行动计划。用户仅追问「现在呢?」,模型应自动补全完整逻辑,但实际输出仍显简略,并以反问结尾,主动性不足。 【GEMINI】模型表现未达预期。在面对用户极简追问时,模型未能展现出作为 AI 助手应有的逻辑补全能力,输出内容过于单薄,缺乏深度。特别是在处理复杂任务的执行记录(工具恢复)和结构化产出(页级提纲)方面,均未能达到专业水准。 【KIMI】模型基本理解了任务核心冲突,但在执行层面存在明显短板:完全遗漏工具链恢复能力的展示,提纲结构降级为普通大纲而非专业页级汇报,且战略建议停留在会议讨论层面缺乏具体行动方案。整体未达到困难档任务对完整性和专业度的要求。
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