Use when the user gives a topic and wants an automated topic-driven narrated explainer, podcast, or knowledge-summary video (Bilibili / YouTube / Xiaohongshu / Douyin / WeChat Channels), or asks to learn visual design patterns from a reference video/image. Trigger when the user mentions creating a knowledge video, narrated explainer, video podcast, or animated infographic-style video from a topic — even if they don't say "video podcast" explicitly. Also trigger when the user wants to regenerate, re-render, rebuild, update, or iterate on a narrated video this skill already produced — e.g. they edited the script/prompt, changed the visuals, or swapped the background music and want the final video remade (reuse the existing videos/{name}/ directory, never start a new project). Do NOT trigger for generic video editing, trimming, format conversion, color grading, or non-narrative video tasks. Produces 4K video via research → script → TTS → Remotion → MP4 + BGM.
npx skills add https://github.com/Agents365-ai/video-podcast-maker --skill video-podcast-maker
> REQUIRED: Load Remotion Best Practices First
>
> This skill depends on remotion-best-practices.
>
> - Pi: read the loaded skill at remotion-best-practices (listed in available skills).
> - Claude Code: invoke remotion-best-practices skill/tool before proceeding.
>
> Not installed? Get it from remotion-dev/skills (docs: remotion.dev/docs/ai/skills).
>
> If remotion-best-practices is not installed, minimum rules: chromium must be available, always wrap 4K content in <Scale4K>, use <TransitionSeries> with linearTiming, and treat audio as the master clock.
Automated pipeline for 4K Bilibili horizontal knowledge videos from a topic. Coding agent + TTS backend + Remotion + FFmpeg.
references/ fileResolve SKILL_DIR to the directory containing this SKILL.md:
SKILL_DIR to that directory before running commands.${CLAUDE_SKILL_DIR} is auto-populated.SKILL_DIR="${SKILL_DIR:-${CLAUDE_SKILL_DIR}}"
# Prerequisites (CLIs + backend env vars)
python3 "${SKILL_DIR}/scripts/check_prereqs.py"
Updates flow through the plugin marketplace (/plugin update); direct git-clone installs use git pull per the README. This skill performs no update checks.
Prereqs failures — see README.md for setup. The check is backend-aware (resolves TTS_BACKEND env → user_prefs.json global.tts.backend → edge default), so only env vars required by the active backend are validated.
First video in a new project? Prefer reusing an existing Remotion project with node_modules/ already installed — creating a fresh project downloads ~2.2 GB of npm packages plus a 90 MB Chrome headless shell (one-time per project). If the user has a project from a previous video, use it. If a fresh project is necessary, run npm install in the background while you do Steps 1-4 (topic research and script writing).
All rendering goes into videos/{name}/ — every output.mp4, final_video.mp4, and thumbnail_*.png lands directly in the per-video directory. Never render to an out/ or dist/ directory; the --public-dir videos/{name}/ convention keeps everything self-contained.
TTS engine — all 11 backends (TTS_BACKEND=edge|azure|cosyvoice|doubao|tencent|baidu|minimax|xunfei|elevenlabs|openai|google) synthesize through the ttscn component skill, which is required: install it under ~/.claude/skills/ttscn or point TTSCN_HOME at its root (Agents365-ai/ttsCN). Each backend still needs only its own API keys (Edge needs none); check_prereqs.py validates both the install and the keys.
> Pi users: ttscn is not bundled with Pi — install Agents365-ai/ttsCN as a Pi skill (its skills/ttscn/ layout is auto-detected) or set TTSCN_HOME; check_prereqs.py verifies the install before TTS.
> Design Learning shortcut: If the user provides a reference video/image or asks to save/list/delete style profiles, see references/design-learning.md instead of running the workflow below.
Detect Auto Mode (default) vs Interactive Mode at workflow start — the Auto-default decision table and per-request overrides are in references/workflow-script.md.
If videos/{name}/ already exists and the user is iterating on a finished or in-progress video, reuse that directory. Do NOT start a new project or a new videos/{newname}/.
Pick the smallest re-run for what actually changed:
| Changed | Re-run | Reuses (don't redo) |
| --------- | -------- | --------------------- |
| Narration script (podcast.txt) | Step 7 (TTS) → Step 8 preview → render+mix | topic research + section design |
| Visuals only (components, layout, colors) | Step 8 preview → render+mix | audio (podcast_audio.wav / timing.json) |
| Background music only | Re-mix BGM | output.mp4 (no re-render) |
| Subtitles only | Step 10.1 finalize | output.mp4 / video_with_bgm.mp4 |
Any re-run that changes what the viewer sees or hears re-enters the Step 8 gate: apply the change, let Studio hot-reload, and wait for a fresh explicit "render 4K" — the previous confirmation does not carry over. A script change shifts every downstream timestamp, so always regenerate timing.json through TTS — never hand-edit it. After any re-run, re-verify:
python3 ${SKILL_DIR}/scripts/verify_output.py videos/{name}/
> Iterating on a finished video? If videos/{name}/ already exists, see Regenerating an Existing Video above for the minimal re-run — do NOT start at Step 1.
At Step 1 start, create one task per step in your agent's tracker. Mark in_progress on start, completed on finish. Files in videos/{name}/ are the durable record — if interrupted, inspect the directory to determine where to resume.
| # | Step | Output | Phase file |
| --- | ------ | -------- | ----------- |
| 1 | Define topic direction | topic_definition.md | workflow-script.md |
| 2 | Research topic | topic_research.md | workflow-script.md |
| 3 | Design 5-7 sections | (in-memory) | workflow-script.md |
| 4 | Write narration script | podcast.txt | workflow-script.md |
| 4.5 | Pronunciation pre-flight (zh-CN) | phonemes.json | workflow-script.md |
| 5 | Asset plan & resolve | assets/manifest.json | workflow-assets.md |
| 6 | Generate thumbnails (16:9 + 4:3) | thumbnail_*.png | workflow-production.md |
| 7 | Generate TTS audio | podcast_audio.wav, timing.json | workflow-production.md |
| 8 | Remotion composition + Studio preview | — | workflow-production.md |
| 9 | Render 4K + mix BGM | output.mp4, video_with_bgm.mp4 | workflow-production.md |
| 10 | Publish info + verify output | publish_info.md, final_video.mp4 | workflow-publish.md |
| 11 | Generate vertical shorts (optional) | shorts/ | workflow-publish.md |
Mandatory stops (bold rows above):
npx remotion studio and wait for user feedback before rendering. NEVER render 4K until the user explicitly confirms ("render 4K" / "render final"). A reply containing adjustment requests is not confirmation — apply the changes, let Studio hot-reload, and ask again. Every round of adjustments needs its own fresh confirmation before Step 9.verify_output.py. MUST pass before declaring the video done. Exit 0 = green; exit 2 = warnings still publishable. Auto-fixes common omissions (creates final_video.mp4 if missing). Validates publish info (title, description, tags, chapters) against the platform matrix — generate it in Steps 5.5 and 10.2. For machine-readable output add --format json.Pre-render audit (recommended) — before Step 8:
python3 ${SKILL_DIR}/scripts/audit_beat_sync.py <Video.tsx> <timing.json>
Flags beats that drift > 1.5s from narration.
Auto Mode: visual self-review. When running in Auto Mode (no user watching Studio), render 3-5 key frame stills before asking for render confirmation:
npx remotion still src/remotion/index.ts <CompositionId> videos/{name}/_review_001.png --public-dir videos/{name}/ --frame=<midpoint_frame>
Pick frames at: hero title (~10% in), a dense section midpoint, and the outro. Read the stills back as images and run the design-guide.md and visual-taste.md checklists against actual rendered output. Catch overflow, contrast, and layout regressions before the 4K render. Delete _review_*.png after review.
| After Step | Check |
| ----------- | ------- |
| 7 (TTS) | podcast_audio.wav plays · timing.json covers all sections · SRT is UTF-8 |
| 9 (Render) | output.mp4 is 3840×2160 · audio-video sync · no black frames |
| 10 (Verify) | verify_output.py exits 0 (or 2 with reviewed warnings) |
| Rule | Requirement |
| ------ | ------------- |
| Single Project | All videos under videos/{name}/ in user's Remotion project. NEVER create a new project per video. |
| 4K Output | 3840×2160 (or 2160×3840 vertical), use scale(2) wrapper over 1920×1080 design space |
| Audio Sync | Audio (podcast_audio.wav + podcast_audio.srt) is the master clock. timing.json MUST be generated from the real TTS output, never hand-estimated. Before rendering, final video duration must match audio within ±0.5s. See Audio-Master Clock & Sync. |
| Thumbnail | MUST generate both 16:9 (1920×1080) AND 4:3 (1200×900) — see design-guide.md |
| Studio Before Render | MUST launch remotion studio for review. NEVER render 4K until user explicitly confirms. Adjustment feedback ≠ confirmation — apply, hot-reload, ask again. |
| --public-dir | Every Remotion command uses --public-dir videos/{name}/. All output files (output.mp4, final_video.mp4, thumbnails) go directly into videos/{name}/ — never an out/ or dist/ dir. |
Visual minimums (text sizes, content width, safe zones, animation safety) live in references/design-guide.md. MUST load before Step 8.
podcast_audio.wav and podcast_audio.srt.podcast.txt → generate_tts.py → podcast_audio.wav + podcast_audio.srt + timing.json → composition → render.timing.json before audio exists. If you already have curated slides, run align_timing_from_srt.py to anchor them to the real SRT.TransitionSeries renders sum(section.duration_frames) - (N-1) * transitionFrames frames. Scale every section proportionally to keep the rendered length equal to timing.total_frames. Do not stuff all overlap frames into the first section. The corrected pattern is in templates/Video.tsx.| When | Check |
| ------ | ------- |
| After Step 7 (TTS) | timing.json.total_duration matches podcast_audio.wav within ±0.5s |
| Before render | Video.tsx scales all sections for transition overlap |
| After render | final_video.mp4 duration matches podcast_audio.wav within ±0.5s |
| Step 10 (verify) | verify_output.py exits 0 and reports green on audio/timing |
If any checkpoint fails, stop. Do not publish.
| Parameter | Horizontal (16:9) | Vertical (9:16) |
| ----------- | ------------------- | ----------------- |
| Resolution | 3840×2160 (4K) | 2160×3840 (4K) |
| Frame rate | 30 fps | 30 fps |
| Encoding | H.264, 16Mbps | H.264, 16Mbps |
| Audio | AAC, 192kbps | AAC, 192kbps |
| Duration | 1-15 min | 60-90s (highlight) |
project-root/ # Remotion project root
├── src/remotion/ # Remotion source (Root.tsx, compositions, index.ts)
├── videos/{video-name}/ # Per-video directory
│ ├── topic_definition.md # Step 1
│ ├── topic_research.md # Step 2
│ ├── podcast.txt # Step 4: narration script
│ ├── phonemes.json # Step 4.5: zh-CN pronunciation overrides
│ ├── assets/manifest.json # Step 5: per-section asset registry
│ ├── publish_info.md # Step 10: title/description/tags
│ ├── podcast_audio.wav # Step 7: TTS audio
│ ├── podcast_audio.srt # Step 7: subtitles
│ ├── timing.json # Step 7: timeline (drives animations)
│ ├── thumbnail_*.png # Step 6
│ ├── output.mp4 # Step 9: 4K render
│ ├── video_with_bgm.mp4 # Step 9: with BGM
│ ├── final_video.mp4 # Step 10: final output
│ └── bgm.mp3 # Background music
└── remotion.config.ts
--public-dir per videoEvery Remotion command uses --public-dir videos/{name}/ — each video's assets stay in its own directory, enabling parallel renders:
npx remotion studio src/remotion/index.ts --public-dir videos/{name}/
npx remotion render ... videos/{name}/output.mp4 --public-dir videos/{name}/ --video-bitrate 16M
npx remotion still ... videos/{name}/thumbnail.png --public-dir videos/{name}/
{video-name}: lowercase English, hyphen-separated (e.g. reference-manager-comparison){section}: lowercase English, underscore-separated, matches [SECTION:xxx]thumbnail_remotion_16x9.png + thumbnail_remotion_4x3.png (or _ai_ prefix for AI-generated)Load on demand — do NOT load all at once:
| File | Load when |
| ------ | ----------- |
| references/workflow-script.md | Steps 1-4 (topic → script) + Execution Modes (Auto vs Interactive) |
| references/natural-narration.md | Load before Step 4 script writing — anti-slop rules for spoken narration (kill list, structural tells, checklist) |
| references/script-polish.md | Load after Step 4 draft is written — deep editing toolkit with 24 EN+ZH before/after patterns, evidence boundaries, quality rubrics |
| references/workflow-assets.md | Step 5, or when the user supplies images/clips or wants stock/AI media |
| references/workflow-assets.md | A section needs a data-chart/infographic animation beyond the component library (transparent overlay via Hyperframes) |
| references/workflow-production.md | Steps 5.5-9.5 (publish info draft → thumbnails → TTS → Remotion → render → BGM mix) |
| references/workflow-publish.md | Steps 10-11 (publish info, verify, shorts) |
| references/platform-matrix.md | Platform-specific behavior (thumbnails, chapters, outro, publish info, shorts) |
| references/design-guide.md | MUST load before Step 8 — visual minimums, typography, animation safety |
| references/visual-taste.md | Load before Step 8 alongside design-guide — design dials, anti-default rules, visual modes, section rhythm |
| references/design-learning.md | User provides a reference video/image, or manages style profiles |
| references/troubleshooting.md | Choosing Azure voice/style, debugging hoarse/glitchy audio |
| references/troubleshooting.md | On error, script/CLI discovery, or user asks about preferences/BGM |
| templates/presets/kinetic-typography/ | Bold type-driven preset (opinion / argument / declaration videos) |
All scripts are reachable through one dispatcher — start with python3 ${SKILL_DIR}/scripts/cli.py --help; full routes and envelope error codes: references/troubleshooting.md.
Mutable state (user_prefs.json, phonemes.json) lives in ~/.video-podcast-maker/ — safe from skill updates. Auto-migrated from the skill directory on first run. Run "show preferences" to view, or "set X Y" to change. Full commands: references/troubleshooting.md.
See references/troubleshooting.md on errors, BGM options, preference learning, design-learning issues.
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Take agents365-ai/video-podcast-maker from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference npm, npx.
Without those the skill loads but fails at the first command.