Skill: x-rayluan/clawlite-video-content-engine (version 1.0.1)

--- name: clawlite-video-content-engine description: | 中文：将 YouTube 视频转化为 ClawLite 营销资产的内容引擎，覆盖摘要、短视频脚本、X thread 与博客输出，支持知识型内容复用与渠道化分发。 日本語：YouTube動画をClawLite向け教育・マーケ配信資産へ再構成。要約、短尺動画、Xスレッド、ブログ出力まで一貫して最適化。 한국어：YouTube 영상을 ClawLite 마케팅 자산으로 재가공하는 콘텐츠 엔진. 요약, 숏폼, X 스레드, 블로그 산출물을 일괄 생성해 채널 확장을 지원. Español：Convierte videos de YouTube en activos de marketing para ClawLite: resumen, guion short-form, hilos de X y posts de blog para reutilización escalable del contenido. --- # ClawLite Video Content Engine Use this skill to convert third-party educational videos into **ClawLite-compatible educational marketing content**. Core principle: - do **not** treat source videos as raw material for plagiarism or blind reposting - treat source videos as **learning inputs** that become: - beginner summaries - practical takeaways - explainer shorts - X threads - LinkedIn/Facebook posts - short blog summaries - soft ClawLite bridge content ## Outcome Turn one source video into a **content pack**: - 1 source summary - 1 beginner translation - 1 short-form video script - 1 X thread - 1 LinkedIn/Facebook post - 1 short blog summary - 1 CTA bridge to ClawLite ## Output location rule Write outputs to a stable folder so the workflow is reusable and auditable. Recommended structure: ```text video-content/ <videoId>/ raw-transcript.md notebooklm-summary.md jk-marketing-asset.md source-note.md short-video-script.md x-thread.md linkedin-post.md blog-summary.md metadata.json ``` At minimum, write: - `notebooklm-summary.md` - `jk-marketing-asset.md` - `source-note.md` - `short-video-script.md` - `x-thread.md` - `blog-summary.md` - `metadata.json` ## Workflow ### Normalization rule NotebookLM output is not the final downstream input. It must be normalized into a **JK / marketing-assets layer** before Elon, Tony, or Jenny consume it. Use this chain: - YouTube / transcript source - raw extraction layer (for example `yt-dlp`) - NotebookLM understanding layer - JK marketing asset layer - Elon / Tony / Jenny execution outputs ### 1. Capture the source video context Record: - title - creator - URL - publish date if useful - duration - main topic - likely beginner pain point If NotebookLM is available, use it for transcript + summary extraction. If NotebookLM is unavailable, create the structure manually from transcript/notes. When using NotebookLM UI automation: - use a screenshot-first workflow - verify the exact input field before typing - avoid generic textarea selectors - confirm source creation before moving to content generation Read `references/notebooklm-automation-guide.md` before automating NotebookLM. ### 2. Build a source note Create a structured source note with: - what the video is about - 3 key takeaways - strongest quote or idea - why it matters for beginners - where setup friction appears - how ClawLite naturally bridges the gap Read `references/source-note-template.md` when building the note. ### 3. Normalize into JK marketing assets Convert the source + NotebookLM understanding into a reusable asset note for downstream lanes. The JK asset should include: - source context - pain point - beginner misunderstanding - 3 key takeaways - strongest idea / quote - angle candidates - hook candidates - ClawLite bridge - Elon social angle - Tony blog angle - Jenny lifecycle angle - source / proof lines This asset layer should become the **shared substrate** for downstream content generation. Read `references/jk-marketing-asset-template.md` when building this layer. ### 4. Translate the source into ClawLite angles Do **not** simply restate the creator video. Create one or more of these angles: - beginner translation - practical summary - “what matters most” summary - “3 takeaways” summary - “too long, didn’t watch” summary - setup-friction reframing Read `references/angle-framework.md` when choosing the angle. ### 5. Create the short-video script Write a 30–90 second short video script with: - hook - 2–3 insights - beginner framing - soft ClawLite bridge - CTA Prefer: - educational tone - real user pain - concise and clear subtitles - no hard sell in the first half Read `references/short-video-template.md` when writing the script. ### 6. Expand into a multi-channel content pack Derive from the same source note and JK marketing asset: - X thread - LinkedIn/Facebook post - short blog summary - optional newsletter blurb Read `references/content-pack-template.md` for the output structure. ### 7. Promote inbox assets into formal marketing-assets Do not leave all value trapped in a one-off source folder. After building the JK asset, normalize reusable pieces into the shared marketing-assets layer. Typical destinations: - pain points → `02-pain-points/` - hooks → `01-hooks/` - angles → `06-angles/` - proof/source lines → `03-proof-points/` - CTA lines → `07-cta/` Rule: - inbox/source asset = working note - marketing-assets = durable shared substrate At minimum, extract from the JK asset: - reusable pain lines - reusable hooks - reusable angle lines - source-backed proof lines Read `references/asset-promotion-guide.md` before promoting shared assets. ### 8. Keep the content compliant Always: - attribute the source creator/video - add original explanation and framing - avoid copying long transcript passages - avoid heavy reuse of original video/audio - keep the result in commentary/education territory, not mirror-reposting Read `references/compliance-and-positioning.md` before finalizing publishable outputs. ## ClawLite bridge rules Use soft bridges such as: - “The concept is powerful. The usual blocker is setup friction.” - “If you want to try this without the setup pain, start with ClawLite.” - “This is the idea. ClawLite makes the first step easier.” Avoid: - overclaiming - hijacking the creator’s work into a hard product ad - turning every summary into aggressive CTA spam ## Recommended output order 1. source note 2. beginner translation 3. short-video script 4. X thread 5. LinkedIn/Facebook post 6. short blog summary 7. ClawLite CTA bridge ## Example use case If given a source video like `https://www.youtube.com/watch?v=fd4k16REDOU`, produce: - a summary note - 3 key beginner takeaways - a 45-second short script - a ClawLite bridge angle - a thread/post/blog content pack ## NotebookLM automation layer Use NotebookLM as the **ingestion layer**, not the final content layer. Its job is to help extract: - transcript understanding - summaries - section structure - notes and source context Your real output should still be a ClawLite content pack. When automating NotebookLM: - screenshot before every action - verify the modal/input target before typing - avoid the sidebar search textarea - re-dispatch input/change events when UI state does not update - verify that the source was actually added before continuing Read `references/notebooklm-automation-guide.md` before doing any NotebookLM UI automation. ## Read next when needed - `references/source-note-template.md` - `references/jk-marketing-asset-template.md` - `references/angle-framework.md` - `references/short-video-template.md` - `references/content-pack-template.md` - `references/asset-promotion-guide.md` - `references/compliance-and-positioning.md` - `references/notebooklm-automation-guide.md`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)