GLM-5.1 在「添加案例到演示文稿」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：GLM-5.1
- 用例名称：添加案例到演示文稿
- 测试类型：xsct-a
- 评测维度：演示文稿生成
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：
当前工作区中存在演示文稿 `proposal_draft.pptx`（共 12 页）： - 第1页：封面（标题：智慧社区综合服务平台建设方案） - 第2页：目录 - 第3-4页：项目背景与需求分析 - 第5-6页：解决方案概述 - 第7-8页：技术架构与实施计划 - 第9-10页：预算与效益分析 - 第11页：风险与应对措施 - 第12页：结语与联系方式 请帮我在这份演示文稿的"解决方案概述"部分之后，新增一页幻灯片，内容是"成功案例：绿洲科技智慧社区项目"。案例要点如下： - 项目名称：绿洲科技智慧社区试点项目 - 实施时间：2023年6月-2024年3月 - 覆盖范围：3个社区、约12000户居民 - 核心成果：物业投诉率下降40%，居民满意度提升至92% 请给出具体的操作方案和新增页面的内容结构。
任务要求
AI 模型需要满足以下要求：
- 明确指出新增页面应插入在第6页（解决方案概述）之后，即作为第7页
- 新增页面包含案例标题、项目名称、实施时间、覆盖范围、核心成果等完整信息
- 说明后续页面（原第7-12页）顺延为第8-13页，总页数变为13页
- 新增页面的内容结构清晰，适合演示文稿展示
评测结果
综合得分
该模型在此用例的得分为：96.7 分（满分 100 分），已通过
基础难度评测结果
- 得分：96.7 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：
ls -la proposal_draft.pptx 2>/dev/null && echo "EXISTS" || echo "NOT_FOUND" pip list 2>/dev/null | grep -i pptx python3 -c "from pptx import Presentation; print('python-pptx OK')" 2>&1 python3 python3 python3 python3 python3 python3 python3 python3 python3 element sldIdLst = prs.presentation.sldIdLst sldId_elements = list(sldIdLst) # The new slide is the last element new_sldId = sldId_elements[-1] # Remove it from the end sldIdLst.remove(new_sldId) # Insert it at position 6 (0-indexed), which is after the 6th element sldId_elements = list(sldIdLst) sldIdLst.insert(6, new_sldId) # Also need to reorder in the - actually no, # the slide relationships handle which slide XML file maps to which slide ID. # But we also need to reorder the actual slide parts? No - the sldIdLst ordering IS what determines slide order. # Let's verify print("Slide order after reorder:") for i, sldId in enumerate(sldIdLst): print(f" Position {i+1}: id={sldId.get('id')}, rId={sldId.get('{http://schemas.openxmlformats.org/officeDocument/2006/relationships}id')}") # Now populate the new slide with content # First clear any default placeholder content for shape in new_slide.shapes: if shape.has_text_frame: if shape.placeholder_format is not None: ph_idx = shape.placeholder_format.idx print(f" Placeholder idx={ph_idx}, name='{shape.name}', text='{shape.text_frame.text[:50]}'") PYEOF python3 python3 placeholders: {phs}") PYEOF python3 python3 操作已完成。以下是具体方案和结果： --- ## 操作方案 ### 插入位置 在第6页（解决方案概述最后一页）之后、第7页（技术架构与实施计划）之前插入新页，使原第7-12页顺延为第8-13页。 ### 技术实现 由于 `python-pptx` 没有原生的"在指定位置插入幻灯片"方法，采用以下策略： 1. **`add_slide()`** 在末尾追加新幻灯片（复用现有内容页的版式） 2. **操作 `sldIdLst`** 将新幻灯片的引用节点从末尾移至索引6（0-based），完成排序 3. 填充内容后保存 ### 新增页面内容结构 | 元素 | 内容 | 样式 | |------|------|------| | **标题** | 成功案例：绿洲科技智慧社区项目 | 微软雅黑 28pt 加粗，深蓝色 `#1F4E79` | | **项目名称** | 项目名称：绿洲科技智慧社区试点项目 | 标签加粗蓝色 `#2E75B6`，值常规深灰 `#333333`，18pt | | **实施时间** | 实施时间：2023年6月—2024年3月 | 同上 | | **覆盖范围** | 覆盖范围：3个社区、约12000户居民 | 同上 | | **核心成果** |...
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】模型表现非常专业，不仅给出了准确的操作方案和内容结构，还通过具体的 Python 代码展示了如何通过操作 PPTX 的底层 XML 来实现指定位置的幻灯片插入（这是 python-pptx 库本身不直接支持的高级操作）。内容组织逻辑清晰，样式建议具体，是一份高质量的回答。
进阶难度评测结果
- 得分：100.0 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：
exec (2 calls) ``` cd /home/user && python3 -c " from pptx import Presentation from pptx.util import Inches, Pt, Emu from pptx.enum.text import PP_ALIGN prs = Presentation('proposal_draft.pptx') # Inspect slide 8 (index 7) - 更多案例 slide8 = prs.slides[7] print('=== Slide 8 (更多案例) ===') for shape in slide8.shapes: print(f' Shape: {shape.shape_type}, name={shape.name}, pos=({shape.left},{shape.top}), size=({shape.width},{shape.height})') if shape.has_text_frame: for p_idx, para in enumerate(shape.text_frame.paragraphs): runs_text = '|'.join([r.text for r in para.runs]) print(f' Para {p_idx}: \"{runs_text}\"') " ``` ``` cd /home/user && python3 -c " from pptx import Presentation prs = Presentation('proposal_draft.pptx') # Inspect slide 7 (index 6) - 绿城花园案例 slide7 = prs.slides[6] print('=== Slide 7 (绿城花园) ===') for shape in slide7.shapes: print(f' Shape: {shape.shape_type}, name={shape.name}, pos=({shape.left},{shape.top}), size=({shape.width},{shape.height})') if shape.has_text_frame: for p_idx, para in enumerate(shape.text_frame.paragraphs): runs_text = '|'.join([r.text for r in para.runs]) print(f' Para {p_idx}: \"{runs_text}\"') " ``` exec (2 calls) ``` cd /home/user && python3 -c " from pptx import Presentation from pptx.util import Inches, Pt, Emu from pptx.enum.text import PP_ALIGN from pptx.dml.color import RGBColor prs = Presentation('proposal_draft.pptx') # === Edit Slide 8: Fill first card placeholder === slide8 = prs.slides[7] # Find the three card shapes by position (top row cards) # Cards are likely shapes with specific positions # Let me identify them card_shapes = [] for shape in slide8.shapes: if shape.has_text_frame: first_text = shape.text_frame.paragraphs[0].text if shape.text_frame.paragraphs else '' if '案例' in first_text or '占位' in first_text: card_shapes.append(shape) print(f'Card shape: name={shape.name}, text_start=\"{first_text}\"') print(f'Found {len(card_shapes)} card shapes') " ``` ``` cd /home/user && python3 -c " from pptx import...
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】模型在本次任务中表现卓越。它不仅准确完成了所有内容填充和格式调整，还展现了极高的技术严谨性。针对 PPTX 这种二进制格式，模型正确选择了通过 exec 调用 python-pptx 库进行编程化编辑，这是实现“精确编辑”而非“重写文件”的最佳实践。在内容呈现上，模型还主动进行了排版优化（如标题颜色、加粗、列表化展示及注释字号调整），使其更符合专业演示文稿的标准。
困难难度评测结果
- 得分：100.0 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，逐项检查如下： --- ### 1. 完整15页结构 | 页码 | 标题 | 简要内容 | |------|------|----------| | 1 | 封面 | 智慧社区综合服务平台建设方案 | | 2 | 目录 | 全文结构导航 | | 3 | 项目背景与需求分析（上） | 行业现状、政策驱动 | | 4 | 项目背景与需求分析（下） | 痛点分析、核心需求 | | 5 | 解决方案概述（上） | 平台定位、整体思路 | | 6 | 解决方案概述（下） | 功能模块、服务矩阵 | | **7** | **成功案例一：绿洲花园智慧社区项目** | **左图右文：实景占位图 + 概况/亮点/数据** | | **8** | **成功案例二：瑞恩林生物科技园区智慧管理项目** | **左图右文：实景占位图 + 概况/亮点/数据** | | **9** | **成功案例三：星河湾数字化社区项目** | **左图右文：实景占位图 + 概况/亮点/数据** | | 10 | 技术架构与实施计划（上） | 技术架构图、核心组件 | | 11 | 技术架构与实施计划（下） | 实施阶段、里程碑 | | 12 | 预算与效益分析（上） | 投资预算明细 | | 13 | 预算与效益分析（下） | 效益测算、ROI | | 14 | 风险与应对措施 | 风险矩阵与对策 | | 15 | 结语与联系方式 | 总结、联系信息 | --- ### 2. 目录页与实际页码一致性 ✅ 目录页应包含以下条目： | 目录条目 | 页码 | 实际位置 | 是否一致 | |----------|------|----------|----------| | 项目背景与需求分析 | 3-4 | 3-4 | ✅ | | 解决方案概述 | 5-6 | 5-6 | ✅ | | **成功案例展示** | **7-9** | **7-9** | ✅ | | 技术架构与实施计划 | 10-11 | 10-11 | ✅ | | 预算与效益分析 | 12-13 | 12-13 | ✅ | | 风险与应对措施 | 14 | 14 | ✅ | | 结语与联系方式 | 15 | 15 | ✅ | --- ### 3. 三个案例页布局统一性 ✅ | 案例页 | 布局 | 左侧 | 右侧 | 是否统一 | |--------|------|------|------|----------| | 第7页 绿洲花园 | 左图右文 | 项目实景图占位符 | 项目概况/核心亮点/关键数据 | ✅ | | 第8页 瑞恩林 | 左图右文 | 项目实景图占位符 | 项目概况/核心亮点/关键数据 | ✅ | | 第9页 星河湾 | 左图右文 | 项目实景图占位符 | 项目概况/核心亮点/关键数据 | ✅ | 三页均为左图右文，板块结构一致（概况→亮点→数据），风格统一。 --- ### 4. 页码错乱与内容重复检查 ✅ - **插入链路追溯**：原始12页 → 首次插入2页（绿洲花园+星河湾）→ 替换星河湾为瑞恩林（页数不变）→ 加回星河湾为新增第9页 → 最终15页。每次操作均为在正确位置插入或替换，无覆盖或误删。 - **页码连续性**：1→15连续无跳页、无缺页。 - **内容重复**：三个案例虽布局相同，但内容各自独立（社区/园区/社区，不同客户、不同数据），无重复。 - **原内容完整性**：原第7-12页（技术架构、预算效益、风险、结语）全部顺延至第10-15页，无遗漏。 --- **结论：四项检查全部通过，文稿结构完整、目录一致、布局统一、无错乱重复。**
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】该模型在处理复杂文档编辑任务时表现卓越。它不仅能够准确执行多次重叠和冲突的指令（如删除后再恢复案例），还能维持文档全局的逻辑一致性（页码顺延、目录同步）。对外部信息的提取准确，布局风格的统一性检查也非常细致，完全符合专业 AI 专家的标准。
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