ppt-creator by daymade/claude-code-skills
npx skills add https://github.com/daymade/claude-code-skills --skill ppt-creator目标:将简单主题转化为可用于演示的高质量幻灯片。当关键信息缺失时,使用最简信息收集表(references/INTAKE.md)来收集上下文或应用安全默认值。然后按照工作流程(references/WORKFLOW.md)生成大纲、幻灯片草稿、图表和演讲者备注。生成后,使用评分标准(references/RUBRIC.md)进行自我评估;如果分数 < 75,则在交付前自动进行最多 2 次迭代优化,直到分数 ≥ 75。最终输出结构请参见交付成果部分。
当用户请求以下内容时使用此技能:
收集意图:如果关键信息缺失,询问10个最简问题(references/INTAKE.md)。如果用户在 2 次提示后未响应,则对每个项目使用安全默认值,并在演讲者备注中明确注明所做的假设。
构建故事结构:应用金字塔原理,建立"一个结论 → 3-5 个顶层理由 → 支持证据"。每张幻灯片使用断言式标题(完整句子),正文内容提供证据(图表/表格/图表/数据点)。模板位于 references/TEMPLATES.md。
选择图表:使用 references/VIS-GUIDE.md 中的图表选择字典为每个要点选择最合适的可视化方式。如果用户提供数据(表格/CSV),可选地调用 scripts/chartkit.py 来生成 PNG 图表;否则,创建占位图表并列出所需数据字段。
布局与样式:遵循 references/STYLE-GUIDE.md 中的字体大小、行间距、留白、对比度、调色板和可访问性(符合 WCAG AA 标准)规范。
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演讲者备注:为每张幻灯片生成 45-60 秒的演讲者备注,结构为:开场 → 核心断言 → 证据解释 → 过渡。
自检与评分:使用 references/CHECKLIST.md 进行交付前检查,然后使用 references/RUBRIC.md 进行评分。如果总分 < 75,找出最弱的 3 个项目并进行优化;重新评分(最多 2 次迭代)。
交付成果(全部保存到 /output/):
* `/output/slides.md`:Markdown 幻灯片(兼容 Marp/Reveal.js),包含断言式标题 + 要点/图表占位符 + 备注
* `/output/assets/*.png`:生成的图表(如适用)
* `/output/notes.md`:完整的演讲者备注和演示大纲
* `/output/refs.md`:引用和数据来源
* `/output/presentation.pptx`:如果 `python-pptx` 可用,则导出为 PPTX;否则,保留 Markdown 格式,并在第一屏包含"一键转换为 PPTX"的说明(不阻碍交付)
当用户请求"完整"或"可用于演示"的交付成果时,ppt-creator 会自动编排整个流程:内容创建 → 数据合成 → 图表生成 → 双路径 PPTX 创建(Marp + document-skills:pptx)→ 图表插入。这通常会交付两个具有不同样式的完整 PPTX 文件供用户比较。
激活:诸如"完整 PPTX"、"最终交付成果"、"可用于演示"等短语 持续时间:4-6 分钟(并行执行) 输出:presentation_marp_with_charts.pptx + presentation_pptx_with_charts.pptx
有关编排的详细信息,请参阅 references/ORCHESTRATION_OVERVIEW.md(从此处开始),然后根据需要导航到专门的指南。
matplotlib/pandas 不可用,则回退到文本 + 占位图表说明。阶段 0 - 归档输入:记录用户的原始请求、使用的默认值和所做的假设。
阶段 1 - 结构化目标:将目标重写为"谁在何时采取什么行动"(清晰的行动号召)。
阶段 2 - 故事线:使用金字塔原理定义"一句话结论 → 3-5 个一级理由 → 证据"。
阶段 3 - 大纲与幻灯片标题:创建 12-15 页的章节骨架。每张幻灯片都有一个断言式标题。
阶段 4 - 证据与图表:使用 VIS-GUIDE 中的图表选择字典。如果提供了数据,则调用 chartkit.py 生成 PNG;否则,创建占位符 + 所需字段列表。
阶段 5 - 布局与可访问性:应用 STYLE-GUIDE 设置字体大小、间距、对比度、调色板;统一单位和小数位数。
阶段 6 - 演讲者备注:为每张幻灯片生成 45-60 秒的备注:开场 → 断言 → 证据解释 → 过渡。
阶段 7 - 自检与评分:运行 CHECKLIST;使用 RUBRIC 评分。如果分数 < 75,专注于最弱的 3 个项目,进行优化,重新评分(最多 2 次迭代)。
阶段 8 - 打包交付成果:生成包含 slides.md / notes.md / refs.md / assets/*.png 的 /output/ 目录。如果 python-pptx 可用,则导出 PPTX。
阶段 9 - 重用说明:在 notes.md 末尾附加"5 步指南,教你用自己的数据/颜色替换"。
最简 10 项问卷(如果缺失则使用默认值):
从"主题"到"可用于演示的输出"的详细分步流程。
幻灯片模板库(断言-证据风格):
数据可视化选择与标签标准:
布局与样式(中性主题,支持品牌替换):
PPT 质量评分标准(100 分;≥ 75 分可交付):每项评分 0-10:
自我评估流程:首先运行 CHECKLIST,然后对每项进行评分,并写出得分最低的 3 个项目 + 改进措施。如果总分 < 75,则应用措施并重新评分(最多 2 次迭代)。
交付前最终质量保证的检查清单。
两个使用示例:
最简图表渲染器,用于 ppt-creator。
用法:
python scripts/chartkit.py \
--data path/to/data.csv \
--type line \
--x date \
--y sales profit \
--out output/assets \
--filename kpi_trend.png \
--title "Monthly KPIs"
注意:
pandas、matplotlib每周安装次数
435
代码仓库
GitHub 星标数
721
首次出现
Jan 20, 2026
安全审计
安装于
opencode373
codex337
gemini-cli334
cursor320
github-copilot299
claude-code294
Goal : Transform a simple topic into a presentation-ready, high-quality slide deck. When key information is missing, use the minimal intake form (references/INTAKE.md) to gather context or apply safe defaults. Then follow the workflow (references/WORKFLOW.md) to produce an outline, slide drafts, charts, and speaker notes. After generation, self-evaluate using the rubric (references/RUBRIC.md); if the score is < 75, automatically refine up to 2 iterations until ≥ 75 before delivery. See Deliverables section for final output structure.
Use this skill when the user requests:
Gather Intent : If critical information is missing, ask the 10 Minimal Questions (references/INTAKE.md). If the user doesn't respond after 2 prompts, use the safe default for each item and clearly note assumptions in speaker notes.
Structure the Story : Apply the Pyramid Principle to establish "one conclusion → 3-5 top-level reasons → supporting evidence." Each slide uses assertion-style headings (complete sentences), with body content providing evidence (charts/tables/diagrams/data points). Templates are in references/TEMPLATES.md.
Choose Charts : Use the Chart Selection Dictionary in references/VIS-GUIDE.md to pick the most appropriate visualization for each point. If the user provides data (tables/CSV), optionally call scripts/chartkit.py to generate PNG charts; otherwise, create placeholder diagrams with a list of required data fields.
Layout & Style: Follow references/STYLE-GUIDE.md for font sizes, line spacing, white space, contrast ratios, color palettes, and accessibility (WCAG AA compliance).
Speaker Notes : Generate 45-60 second speaker notes for each slide, structured as: opening → core assertion → evidence explanation → transition.
Self-Check & Score: Use references/CHECKLIST.md for a pre-flight check, then score with references/RUBRIC.md. If total score < 75, identify the weakest 3 items and refine; repeat scoring (max 2 iterations).
Deliverables (all saved to /output/):
/output/slides.md: Markdown slides (Marp/Reveal.js compatible), with assertion-style headings + bullet points/chart placeholders + notes/output/assets/*.png: Generated charts (if applicable)/output/notes.md: Full speaker notes and delivery outline/output/refs.md: Citations and data sources/output/presentation.pptx: If python-pptx is available, export to PPTX; otherwise, keep Markdown and include instructions for "one-click conversion to PPTX" in the first screen (does not block delivery)When the user requests a "complete" or "presentation-ready" deliverable, ppt-creator automatically orchestrates the full pipeline: content creation → data synthesis → chart generation → dual-path PPTX creation (Marp + document-skills:pptx) → chart insertion. This typically delivers TWO complete PPTX files with different styling for user comparison.
Activation : Phrases like "complete PPTX", "final deliverable", "ready for presentation" Duration : 4-6 minutes (parallel execution) Output : presentation_marp_with_charts.pptx + presentation_pptx_with_charts.pptx
For orchestration details, see references/ORCHESTRATION_OVERVIEW.md (start here), then navigate to specialized guides as needed.
matplotlib/pandas are unavailable, fall back to text + placeholder diagram instructions.Stage 0 - Archive Input : Record user's original request, defaults used, and assumptions made.
Stage 1 - Structure Goals : Rewrite the goal into "who takes what action when" (clear CTA).
Stage 2 - Storyline : Use Pyramid Principle to define "one-sentence conclusion → 3-5 first-level reasons → evidence."
Stage 3 - Outline & Slide Titles: Create a 12-15 slide chapter skeleton. Each slide has one assertion-style heading.
Stage 4 - Evidence & Charts: Use the Chart Selection Dictionary from VIS-GUIDE. If data is provided, call chartkit.py to generate PNGs; otherwise, create placeholder + required field list.
Stage 5 - Layout & Accessibility: Apply STYLE-GUIDE for font sizes, spacing, contrast ratios, color palettes; unify units and decimal places.
Stage 6 - Speaker Notes : Generate 45-60 second notes per slide: opening → assertion → evidence explanation → transition.
Stage 7 - Self-Check & Scoring: Run CHECKLIST; score with RUBRIC. If score < 75, focus on weakest 3 items, refine, re-score (max 2 iterations).
Stage 8 - Package Deliverables : Generate /output/ directory with slides.md / notes.md / refs.md / assets/*.png. If python-pptx is available, export PPTX.
Stage 9 - Reuse Instructions : Append a "5-step guide to replace data/colors with your own" at the end of notes.md.
Minimal 10-Item Questionnaire (use defaults if missing):
Detailed step-by-step process from "topic" to "presentation-ready output."
Slide Template Library (assertion-evidence style):
Data Visualization Selection & Labeling Standards:
Layout & Style (neutral theme, supports brand replacement):
PPT Quality Scoring Rubric (100 points; ≥ 75 to deliver): Each item scored 0-10:
Self-evaluation process: Run CHECKLIST first, then score each item and write top 3 low-scoring items + improvement actions. If total < 75, apply actions and re-score (max 2 iterations).
Pre-flight checklist for final quality assurance before delivery.
Two Usage Examples :
Minimal chart renderer for ppt-creator.
Usage :
python scripts/chartkit.py \
--data path/to/data.csv \
--type line \
--x date \
--y sales profit \
--out output/assets \
--filename kpi_trend.png \
--title "Monthly KPIs"
Notes :
pandas, matplotlibWeekly Installs
435
Repository
GitHub Stars
721
First Seen
Jan 20, 2026
Security Audits
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Installed on
opencode373
codex337
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cursor320
github-copilot299
claude-code294
Lark Base CLI 使用指南:数据查询、公式与查找字段操作详解
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