video-understanding 是做什麼的?
Agent 技能:時間戳記畫面 + 本地 Whisper SRT → 產生關聯視覺與語音的 understanding.md。
Agent 技能:時間戳記畫面 + 本地 Whisper SRT → 產生關聯視覺與語音的 understanding.md。
這是一個 AI Agent 技能,專門用來分析影片內容。它能將影片分割成含時間戳記的畫面(timestamped frames),並透過本地執行的 Whisper 語音辨識引擎將語音轉換為 SRT 字幕檔。最終,它會產出一個名為 understanding.md 的 Markdown 檔案,該檔案會將畫面中的視覺元素與對應時間點的語音內容相互關聯,提供結構化的影片理解摘要。此技能支援所有可執行 Python 與 ffmpeg 的命令列環境或 Agent 框架(如 Claude Code、Cursor、Codex 等)。對開發者與 AI Agent 使用者而言,這項技能極具價值,能自動化影片分析流程,避免手動觀看與轉寫,大幅提升影片內容審查、自動摘要或後製處理的效率。其運作方式依賴本地 Whisper 模型確保隱私與離線可用性,並利用 ffmpeg 進行精確的畫面擷取,最後以簡單的 Markdown 格式輸出,易於整合至其他工具或工作流程中。
npx skills add stevederico/video-understandingAgent 技能:時間戳記畫面 + 本地 Whisper SRT → 產生關聯視覺與語音的 understanding.md。
Extract frames or short clips from videos using ffmpeg.
Summarize or transcribe URLs, YouTube/videos, podcasts, articles, transcripts, PDFs, and local files.
Use when testing, fixing, or extending the OpenClaw Control UI GUI with Vitest + Playwright end-to-end checks, mocked Gateway WebSocket flows, mocked dashboard runs, screenshots/videos, or agent-verifiable browser proof.
Obra superpowers agent skills.
See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio...
End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.