wjs-overlaying-video
Use when the user has one or more video clips and wants to add post-production on top — AI-generated cover as first frame, HTML/CSS captions synced to SRT, kinetic illustration overlays at hook moments, chapter chips, end-card CTA, or any other timed motion graphics. Most often used as the downstream of `/wjs-segmenting-video` — pick up where that skill stopped (raw cropped clip + per-clip SRT) and produce the upload-ready MP4. Backed by HyperFrames so everything compiles to ONE final encode — no cascade of re-encodes. Triggers — "加封面", "加字幕", "加动画", "加 CTA", "做后期", "post-production", "title c
npx skills add jianshuo/claude-skills --skill wjs-overlaying-video --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# wjs-overlaying-video Post-production for a video clip: cover, captions, illustrations, CTA, custom motion graphics — all composed in ONE HyperFrames project and rendered in a SINGLE final encode. No cascade of decodes/re-encodes (each cascade pass degrades quality and burns time). ## When to use - **Downstream of `/wjs-segmenting-video`** — the segmentation skill hands you cropped clips + per-clip SRTs; this skill turns them into upload-ready MP4s with cover/captions/illustrations/CTA. - User has a finished video and wants to dress it up with motion graphics: opening hook, key-quote callout, closing slogan, chapter cards, AI-generated cover as first frame. - User wants HTML/CSS-quality captions on a video (kinetic word-by-word highlighting, custom fonts, large outlined text, seekable per cue). - User wants illustration overlays at specific hook moments — diagrams, big text emphasis, flow charts. **Don't use** for: - Splitting one long video into clips → use `/wjs-segmenting-video`. - Creating the source SRT → use `/wjs-transcribing-audio` (then `/wjs-translating-subtitles` if you need a different language). - Full HyperFrames productions where the source isn't a fixed video → use
- When to use
- What this skill IS — and IS NOT
- The pipeline
- Color: tone-map HLG/HDR source → SDR BEFORE compositing
- Version stamp (every output)
- Standard overlay types (the 6 building blocks)
- 1. cover — full-frame AI image as first frame
- 2. caption — 关键词高亮 captions (字幕风格 03) synced to SRT
- 3. chapter — top-left chapter chip (4s reveal then fade)
- 4. stack illustration — top-right vertical list card
- 5. hammer illustration — center-frame big equation/text overlay
- 6. cta — end-card with channel CTA
- Legacy types (for one-off overlays on a single video)
- Workflow A — Post-segmentation preset (most common)
For 1080×1920 vertical output (视频号 / 抖音): make_cover.py --segments S.json --out output/ --size 1024x1792 [--single N] For 1920×1080 horizontal output (YouTube / B站): make_cover.py --segments S.json --out output/ --size 1536x1024 For vertical 9:16 output (视频号 / 抖音): python3 ~/.claude/skills/wjs-segmenting-video/scripts/make_cover.py \ Verify segment 1's cover; then batch: python3 references/build_hf_clips.py # scaffolds all projects for n in 01 02 03 04 05; do cd "hf_clip_$n/1080"
What does the wjs-overlaying-video skill do?
Use when the user has one or more video clips and wants to add post-production on top — AI-generated cover as first frame, HTML/CSS captions synced to SRT, kinetic illustration overlays at hook moments, chapter chips, end-card CTA, or any other timed motion graphics. Most often used as the downstream of `/wjs-segmenting-video` — pick up where that skill stopped (raw cropped clip + per-clip SRT) and produce the upload-ready MP4. Backed by HyperFrames so everything compiles to ONE final encode — no cascade of re-encodes. Triggers — "加封面", "加字幕", "加动画", "加 CTA", "做后期", "post-production", "title c
How do I install it?
Run `npx skills add jianshuo/claude-skills --skill wjs-overlaying-video --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From jianshuo/claude-skills, a repository with 112 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.