video-podcast-maker

name	video-podcast-maker
description	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 talking-head topic 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.
argument-hint	[topic]
effort	high
author	Agents365-ai
category	Content Creation
version	2.4.1
created	"2025-01-27T00:00:00.000Z"
updated	"2026-06-28T00:00:00.000Z"
bilibili	https://space.bilibili.com/441831884
github	https://github.com/Agents365-ai/video-podcast-maker
dependencies	["remotion-best-practices"]
metadata	{"openclaw":{"requires":{"bins":["python3","ffmpeg","node","npx"]},"primaryEnv":"AZURE_SPEECH_KEY","emoji":"🎬","homepage":"https://github.com/Agents365-ai/video-podcast-maker","os":["macos","linux"],"install":[{"kind":"brew","formula":"ffmpeg","bins":["ffmpeg"]},{"kind":"uv","package":"edge-tts","bins":["edge-tts"]}]}}

REQUIRED: Load Remotion Best Practices First

This skill depends on remotion-best-practices. You MUST invoke it before proceeding:

Invoke the skill/tool named: remotion-best-practices

Video Podcast Maker

Automated pipeline for 4K Bilibili horizontal knowledge videos from a topic. Coding agent + TTS backend + Remotion + FFmpeg.

Contents

• Bootstrap — update check + prerequisites (run before Step 1)
• Execution Modes — Auto vs Interactive, default decisions
• Regenerating an Existing Video — reuse videos/{name}/ to iterate on a finished video
• Workflow — the 15 steps + phase-file pointers + mandatory stops
• Hard Rules — non-negotiable production constraints + output specs
• Per-Video Layout — directory structure, --public-dir, naming
• Additional Resources — when to load each references/ file
• User Preferences
• Troubleshooting

---

Bootstrap

Resolve SKILL_DIR to the directory containing this SKILL.md. If your agent exposes a built-in skill directory variable (e.g. ${CLAUDE_SKILL_DIR}), map it to SKILL_DIR.

SKILL_DIR="${SKILL_DIR:-${CLAUDE_SKILL_DIR}}"

# 1. Update check (notify-only, throttled to 24h)
"${SKILL_DIR}/scripts/check_update.sh"

# 2. Prerequisites (CLIs + backend env vars)
python3 "${SKILL_DIR}/scripts/check_prereqs.py"

check_update.sh output:

• UPDATE_AVAILABLE vX.Y.Z -> vA.B.C — tell the user the version delta and ask before running git -C "${SKILL_DIR}" pull --ff-only. Notify-only by design — never pull without consent (the skill directory belongs to the user).
• UP_TO_DATE / SKIPPED_RECENT_CHECK / MANUAL_INSTALL — continue silently.

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.

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.

---

Execution Modes

Detect at workflow start:

• "Make a video about..." / no special instructions → Auto Mode (default)
• "I want to control each step" / "interactive" → Interactive Mode

Auto Mode defaults

Full pipeline with sensible defaults. Mandatory stop at Step 9 (Studio review); Step 10 (4K render) only fires when the user says "render 4K" / "render final".

Step	Decision	Auto Default
3	Title position	top-center
5	Media assets	Skip (text-only animations)
7	Thumbnail method	Remotion-generated (16:9 + 4:3)
9	Outro animation	Pre-made MP4 (white/black by theme)
12	Subtitle method	Remotion-native (skip legacy FFmpeg burn)
14	Cleanup	Auto-clean temp files

Override any default in the initial request:

• "make a video about AI, burn subtitles" → auto + subtitles on
• "use dark theme, AI thumbnails" → auto + dark + imagen
• "need screenshots" → auto + media collection enabled

Interactive Mode

Prompts at each decision point.

---

Regenerating an Existing Video

If videos/{name}/ already exists and the user is iterating on a finished or in-progress video — "regenerate", "re-render", "rebuild", "I edited the script/prompt", "update the video", "change the BGM" — reuse that directory. Do NOT start a new project or a new videos/{newname}/; that is the Single Project rule applied to iteration, and starting fresh is the most common mistake here.

Pick the smallest re-run for what actually changed. Every command targets the same videos/{name}/, and every Remotion command keeps --public-dir videos/{name}/:

Changed	Re-run	Reuses (don't redo)
Narration script (podcast.txt)	Step 8 (generate_tts.py --output-dir videos/{name}) → Step 10 render → Step 11 BGM	topic research + section design
Visuals only (components, layout, colors, props)	Step 10 render	podcast_audio.wav / timing.json (audio unchanged)
Background music only	Step 11 mix	output.mp4 (no re-render)
Subtitles only	Step 12	output.mp4 / video_with_bgm.mp4

A script change shifts every downstream timestamp, so always regenerate timing.json through TTS — never hand-edit it (see Audio-Master Clock). After any re-run, re-verify:

python3 ${SKILL_DIR}/scripts/verify_output.py videos/{name}/

Cleanup only removes TTS temp files, never output.mp4 / video_with_bgm.mp4 — so BGM/subtitle re-runs avoid a full ~8-min re-render.

---

Workflow

Iterating on a finished video? If videos/{name}/ already exists and the user wants to regenerate after a change, do NOT start at Step 1 — see Regenerating an Existing Video for the minimal re-run.

At Step 1 start, create one task per step in your agent's tracker (Claude Code TaskCreate / Codex todo list / equivalent). 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	Collect media (Auto: skip)	media_manifest.json	workflow-production.md
6	Generate publish info (Part 1)	publish_info.md	workflow-production.md
7	Generate thumbnails (16:9 + 4:3)	thumbnail_*.png	workflow-production.md
8	Generate TTS audio	podcast_audio.wav, timing.json	workflow-production.md
9	Remotion composition + Studio preview	—	workflow-production.md
10	Render 4K video (only on user request)	output.mp4	workflow-production.md
11	Mix background music	video_with_bgm.mp4	workflow-production.md
12	Finalize (optional legacy subtitle burn)	final_video.mp4	workflow-publish.md
13	Complete publish info (Part 2)	chapter timestamps	workflow-publish.md
14	Verify output (scripts/verify_output.py)	—	workflow-publish.md
15	Generate vertical shorts (optional)	shorts/	workflow-publish.md

Mandatory stops (bold rows above):

• Step 9 — Studio review. MUST launch npx remotion studio and wait for user feedback before rendering. NEVER render 4K until the user explicitly confirms ("render 4K" / "render final").
• Step 14 — 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). For machine-readable output add --format json (auto when piped).

Pre-render audit (recommended) — before Step 9:

python3 ${SKILL_DIR}/scripts/audit_beat_sync.py <Video.tsx> <timing.json>

Flags beats that drift > 1.5s from narration. Especially important for kinetic-typography videos.

Validation Checkpoints

After Step	Check
8 (TTS)	podcast_audio.wav plays · timing.json covers all sections · SRT is UTF-8
10 (Render)	output.mp4 is 3840×2160 · audio-video sync · no black frames
14 (Verify)	verify_output.py exits 0 (or 2 with reviewed warnings)

---

Hard Rules

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.
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.
--public-dir	Every Remotion command uses --public-dir videos/{name}/

Visual minimums (text sizes, content width, safe zones, animation safety) live in references/design-guide.md. MUST load before Step 9.

Audio-Master Clock & Sync

Golden rules

1. Audio is the master clock. Every slide start, subtitle, progress-bar chapter, and animation beat is derived from podcast_audio.wav and podcast_audio.srt.
2. Generate timing from TTS, not from text estimates. The canonical pipeline is:

   podcast.txt (final)
     → generate_tts.py
     → podcast_audio.wav + podcast_audio.srt + timing.json
     → Remotion composition
     → render
   

3. Never hand-write timing.json before audio exists. If you already have curated slides, run align_timing_from_srt.py to anchor them to the real SRT, or add a "section" field to each slide and then run it.
4. Compensate TransitionSeries overlap. TransitionSeries renders sum(section.duration_frames) - (N-1) * transitionFrames frames. To keep the rendered length equal to timing.total_frames, scale every section proportionally; do not stuff all overlap frames into the first section. The corrected pattern is in templates/Video.tsx.

Mandatory sync checkpoints

When	Check	Command / Action
After Step 8	timing.json.total_duration matches podcast_audio.wav within ±0.5s	ffprobe -show_entries format=duration podcast_audio.wav
Before Step 10	Video.tsx scales all sections for transition overlap	Inspect the compensatedSections calculation
After Step 10/12	final_video.mp4 duration matches podcast_audio.wav within ±0.5s	ffprobe -show_entries format=duration final_video.mp4
Step 14	verify_output.py exits 0 and reports green on audio/timing	python3 ${SKILL_DIR}/scripts/verify_output.py videos/<name>/

If any checkpoint fails, stop. Do not publish.

Output Specs

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)

---

Per-Video Layout

project-root/                           # Remotion project root
├── src/remotion/                       # Remotion source (Root.tsx, compositions, index.ts)
├── videos/{video-name}/                # Per-video assets (the agent's working dir)
│   ├── 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
│   ├── podcast_audio.wav               # Step 8: TTS audio
│   ├── podcast_audio.srt               # Step 8: subtitles
│   ├── timing.json                     # Step 8: timeline (drives animations)
│   ├── thumbnail_*.png                 # Step 7
│   ├── output.mp4                      # Step 10: 4K render (no BGM)
│   ├── video_with_bgm.mp4              # Step 11
│   ├── final_video.mp4                 # Step 12: final output
│   └── bgm.mp3                         # Background music
└── remotion.config.ts

--public-dir per video

Remotion commands MUST use --public-dir videos/{name}/ — each video's assets stay in its own directory, no copy to public/. Enables parallel renders.

npx remotion studio src/remotion/index.ts --public-dir videos/{name}/
npx remotion render src/remotion/index.ts CompositionId videos/{name}/output.mp4 --public-dir videos/{name}/ --video-bitrate 16M
npx remotion still src/remotion/index.ts Thumbnail16x9 videos/{name}/thumbnail.png --public-dir videos/{name}/

Naming

• Video name {video-name}: lowercase English, hyphen-separated (e.g. reference-manager-comparison)
• Section name {section}: lowercase English, underscore-separated, matches [SECTION:xxx]
• Thumbnail naming (16:9 AND 4:3 both required):

Type	16:9	4:3
Remotion	thumbnail_remotion_16x9.png	thumbnail_remotion_4x3.png
AI	thumbnail_ai_16x9.png	thumbnail_ai_4x3.png

---

Additional Resources

Load on demand — do NOT load all at once:

File	Load when
references/workflow-script.md	Steps 1-4 (topic → script)
references/workflow-production.md	Steps 5-11 (media → TTS → Remotion → render → BGM)
references/workflow-publish.md	Steps 12-15 (subtitles, publish, cleanup, shorts)
references/design-guide.md	MUST load before Step 9 — visual minimums, typography, animation safety
references/design-learning.md	User provides a reference video/image, or manages style profiles
references/azure-tts-pitfalls.md	Choosing Azure voice/style, debugging hoarse/glitchy audio
references/troubleshooting.md	On error, or user asks about preferences/BGM
templates/presets/kinetic-typography/	Bold type-driven preset (opinion / argument / declaration videos)
examples/	Reference for composition structure and timing.json format

Script suite dispatcher

All scripts under ${SKILL_DIR}/scripts/ are reachable through one hierarchical entry point:

python3 ${SKILL_DIR}/scripts/cli.py --help                  # list resources
python3 ${SKILL_DIR}/scripts/cli.py <resource> --help       # list actions
python3 ${SKILL_DIR}/scripts/cli.py <resource> <action> --help    # forwards to underlying script
python3 ${SKILL_DIR}/scripts/cli.py schema [<method>]       # JSON parameter schema

Routes: tts run|validate, verify, align, audit beats, shorts gen, design list|show|delete|add, prereqs, prefs get|migrate|backend|bgm-path, schema [<method>]. Direct script invocation (python3 scripts/<name>.py ...) keeps working — the dispatcher is additive.

---

User Preferences

Skill auto-learns and applies preferences. Full commands and learning details: references/troubleshooting.md.

• Storage: user_prefs.json (auto-created from user_prefs.template.json, schema in prefs_schema.json).
• Priority: Root.tsx defaults < global < topic_patterns[type] < current instructions.
• User commands: "show preferences" · "reset preferences" · "save as X default".

---

Troubleshooting

See references/troubleshooting.md on errors, BGM options, preference learning, design-learning issues.