ppt-creator 是做什麼的？
從主題或文件建立專業的簡報投影片。生成帶有資料圖表、演講者備註和完整 PPTX 檔案的結構化內容。運用說服性故事創作原則（金字塔原理、斷言-證據法）。支援多種格式（Marp、PowerPoint）。適用於簡報、提案、投影片或主題演講。
從主題或文件建立專業的簡報投影片。生成帶有資料圖表、演講者備註和完整 PPTX 檔案的結構化內容。運用說服性故事創作原則（金字塔原理、斷言-證據法），支援多種格式（Marp、PowerPoint）。適用於簡報、提案、投影片或主題演講。
此技能可讓 AI 助手根據使用者提供的主題或文件，自動生成結構化的簡報內容。它不僅能產出包含資料驅動圖表與演講者備註的文字草稿，還能直接輸出完整的 PPTX 檔案，大幅節省從零開始設計簡報的時間。此技能特別內建了金字塔原理與斷言-證據法等專業的說服性故事創作框架，確保最終簡報不僅美觀，更具邏輯說服力。無論是用於內部報告、客戶提案還是大型主題演講，此技能都能協助快速產出專業級簡報。它支援 Marp 與 PowerPoint 等多種輸出格式，讓使用者能彈性選擇適合的平台進行後續編輯與播放。
npx skills add https://github.com/daymade/claude-code-skills/tree/main/skills/ppt-creatorInstalled? Explore more 寫作與編輯 skills: steipete/notion, langchain-ai/langchain, bytedance/podcast-generation · View all 6 →
從主題或文件建立專業的簡報投影片。生成帶有資料圖表、演講者備註和完整 PPTX 檔案的結構化內容。運用說服性故事創作原則（金字塔原理、斷言-證據法）。支援多種格式（Marp、PowerPoint）。適用於簡報、提案、投影片或主題演講。
This repo contains 9 individual skills — each has its own dedicated page.
>- Generates Chinese/Japanese speech with StepFun's Contextual TTS — default stepaudio-2.5-tts, stepaudio-3-tts for whisper/inline-() prosody. Replaces step-tts-2's voice_label with natural-language instruction. Use for emotional/prosody-controlled synthesis, batch voice lines, migrating from step-tts-2, or cloned voices (2.5/step-tts-2, not v3). Triggers on 阶跃 TTS, 语音合成, 配音. Not for transcription (use stepfun-asr).
This skill should be used when comparing two videos to analyze compression results or quality differences. Generates interactive HTML reports with quality metrics (PSNR, SSIM) and frame-by-frame visual comparisons. Triggers when users mention "compare videos", "video quality", "compression analysis", "before/after compression", or request quality assessment of compressed videos.
Download YouTube videos and HLS streams (m3u8) from platforms like Mux, Vimeo, etc. using yt-dlp and ffmpeg. Use this skill when users request downloading videos, extracting audio, handling protected streams with authentication headers, or troubleshooting download issues like nsig extraction failures, 403 errors, or cookie extraction problems.
Entry point for local AI conversation history across providers. Routes a request to the one skill that owns it, by platform (Claude Code, OpenAI Codex, Kimi CLI) and action (read evidence vs continue interrupted work), and owns the one job none of them own alone: a single inventory spanning all three providers. Use when the provider is unknown or plural ("our history", "what have I been working on", "which chats did I have"), when the user wants Kimi CLI history at all, when it is unclear whether they need evidence or resumption, or when they ask for this skill by name. Vague recall that names no platform ("we discussed this once, when was it?") belongs here rather than to a single-provider reader, because a Claude-only answer to an unscoped question cannot support an absence claim. When the platform and the action are both already clear, load that executor skill directly instead — except Kimi CLI, which has no reader or continuation skill of its own and always routes through here.
Transform vague prompts into precise, well-structured specifications using EARS (Easy Approach to Requirements Syntax) methodology. This skill should be used when users provide loose requirements, ambiguous feature descriptions, or need to enhance prompts for AI-generated code, products, or documents. Triggers include requests to "optimize my prompt", "improve this requirement", "make this more specific", or when raw requirements lack detail and structure.
This skill should be used when establishing comprehensive QA testing processes for any software project. Use when creating test strategies, writing test cases following Google Testing Standards, executing test plans, tracking bugs with P0-P4 classification, calculating quality metrics, or generating progress reports. Includes autonomous execution capability via master prompts and complete documentation templates for third-party QA team handoffs. Implements OWASP security testing and achieves 90% coverage targets.
Reads, searches, and exports local Claude Code history without resuming work. Covers recent session inventory, exact session timelines, verbatim human input including queued mid-turn prompts, full-event keyword search, hybrid recall when wording changed, end-state triage, and deleted-file recovery across active Claude homes plus registered archives. Use whenever the user asks what they or Claude said, wants a Claude Code session ID or original context, remembers prior work vaguely, needs an old file from a transcript, or must prove what a Claude session contained before continuing it. Also owns the only Kimi CLI surface, via its Kimi inventory and search flags. For Codex history use read-codex-history; when the request names no platform at all or spans providers, start at local-conversation-history.
Reads, searches, and exports local OpenAI Codex history without continuing the old task. Lists recent Codex sessions, extracts exact prompt-ledger inputs by Session, locates a rollout by verified session_meta identity, reconstructs one chronological user/assistant timeline with fork and compaction lineage, and performs bounded keyword search across live and archived rollouts. Use whenever the user asks what they told Codex, wants recent original inputs, a Codex Session ID, full prior context, fork ancestry, or evidence of what a Codex run did. For Claude Code history use read-claude-code-history.
Fetch Twitter/X post content including long-form Articles with full images and metadata. Use when Claude needs to retrieve tweet/article content, author info, engagement metrics, and embedded media. Supports individual posts and X Articles (long-form content). Automatically downloads all images to local attachments folder and generates complete Markdown with proper image references. Preferred over Jina for X Articles with images.
Notion CLI/API for pages, Markdown content, data sources, files, comments, search, Workers, and raw API calls.
The agent engineering platform.
Use this skill when the user requests to generate, create, or produce podcasts from text content. Converts written content into a two-host conversational podcast audio format with natural dialogue.
Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.
Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.
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