MCPInstall

video-podcast-maker

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.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/agents365-ai/365-skills --skill video-podcast-maker
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads video-podcast-maker automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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.

Video Podcast Maker

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

Contents


Bootstrap

Resolve SKILL_DIR to the directory containing this SKILL.md:

  • Pi: the agent knows the skill path from the loaded skill list — set SKILL_DIR to that directory before running commands.
  • Claude Code: ${CLAUDE_SKILL_DIR} is auto-populated.
SKILL_DIR="${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.


Execution Modes

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.


Regenerating an Existing Video

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:

ChangedRe-runReuses (don't redo)
Narration script (podcast.txt)Step 7 (TTS) → Step 8 preview → render+mixtopic research + section design
Visuals only (components, layout, colors)Step 8 preview → render+mixaudio (podcast_audio.wav / timing.json)
Background music onlyRe-mix BGMoutput.mp4 (no re-render)
Subtitles onlyStep 10.1 finalizeoutput.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}/

Workflow

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.

#StepOutputPhase file
1Define topic directiontopic_definition.mdworkflow-script.md
2Research topictopic_research.mdworkflow-script.md
3Design 5-7 sections(in-memory)workflow-script.md
4Write narration scriptpodcast.txtworkflow-script.md
4.5Pronunciation pre-flight (zh-CN)phonemes.jsonworkflow-script.md
5Asset plan & resolveassets/manifest.jsonworkflow-assets.md
6Generate thumbnails (16:9 + 4:3)thumbnail_*.pngworkflow-production.md
7Generate TTS audiopodcast_audio.wav, timing.jsonworkflow-production.md
8Remotion composition + Studio preview—workflow-production.md
9Render 4K + mix BGMoutput.mp4, video_with_bgm.mp4workflow-production.md
10Publish info + verify outputpublish_info.md, final_video.mp4workflow-publish.md
11Generate vertical shorts (optional)shorts/workflow-publish.md

Mandatory stops (bold rows above):

  • Step 8 — 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"). 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.
  • Step 10 — 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.

Validation Checkpoints

After StepCheck
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)

Hard Rules

RuleRequirement
Single ProjectAll videos under videos/{name}/ in user's Remotion project. NEVER create a new project per video.
4K Output3840×2160 (or 2160×3840 vertical), use scale(2) wrapper over 1920×1080 design space
Audio SyncAudio (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.
ThumbnailMUST generate both 16:9 (1920×1080) AND 4:3 (1200×900) — see design-guide.md
Studio Before RenderMUST launch remotion studio for review. NEVER render 4K until user explicitly confirms. Adjustment feedback ≠ confirmation — apply, hot-reload, ask again.
--public-dirEvery 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.

Audio-Master Clock & Sync

Golden rules

  1. Audio is the master clock. Every slide start, subtitle, chapter, and animation beat is derived from podcast_audio.wav and podcast_audio.srt.
  2. Generate timing from TTS, not from text estimates. Pipeline: podcast.txt → generate_tts.py → podcast_audio.wav + podcast_audio.srt + timing.json → 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.
  4. Compensate TransitionSeries overlap. 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.

Mandatory sync checkpoints

WhenCheck
After Step 7 (TTS)timing.json.total_duration matches podcast_audio.wav within ±0.5s
Before renderVideo.tsx scales all sections for transition overlap
After renderfinal_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.

Output Specs

ParameterHorizontal (16:9)Vertical (9:16)
Resolution3840×2160 (4K)2160×3840 (4K)
Frame rate30 fps30 fps
EncodingH.264, 16MbpsH.264, 16Mbps
AudioAAC, 192kbpsAAC, 192kbps
Duration1-15 min60-90s (highlight)

Per-Video Layout

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 video

Every 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}/

Naming

  • Video name {video-name}: lowercase English, hyphen-separated (e.g. reference-manager-comparison)
  • Section name {section}: lowercase English, underscore-separated, matches [SECTION:xxx]
  • Thumbnails (16:9 AND 4:3 both required): thumbnail_remotion_16x9.png + thumbnail_remotion_4x3.png (or _ai_ prefix for AI-generated)

Additional Resources

Load on demand — do NOT load all at once:

FileLoad when
references/workflow-script.mdSteps 1-4 (topic → script) + Execution Modes (Auto vs Interactive)
references/natural-narration.mdLoad before Step 4 script writing — anti-slop rules for spoken narration (kill list, structural tells, checklist)
references/script-polish.mdLoad after Step 4 draft is written — deep editing toolkit with 24 EN+ZH before/after patterns, evidence boundaries, quality rubrics
references/workflow-assets.mdStep 5, or when the user supplies images/clips or wants stock/AI media
references/workflow-assets.mdA section needs a data-chart/infographic animation beyond the component library (transparent overlay via Hyperframes)
references/workflow-production.mdSteps 5.5-9.5 (publish info draft → thumbnails → TTS → Remotion → render → BGM mix)
references/workflow-publish.mdSteps 10-11 (publish info, verify, shorts)
references/platform-matrix.mdPlatform-specific behavior (thumbnails, chapters, outro, publish info, shorts)
references/design-guide.mdMUST load before Step 8 — visual minimums, typography, animation safety
references/visual-taste.mdLoad before Step 8 alongside design-guide — design dials, anti-default rules, visual modes, section rhythm
references/design-learning.mdUser provides a reference video/image, or manages style profiles
references/troubleshooting.mdChoosing Azure voice/style, debugging hoarse/glitchy audio
references/troubleshooting.mdOn 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.


User Preferences

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.


Troubleshooting

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

FAQ

What does the video-podcast-maker skill do?

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.

How do I install video-podcast-maker?

Run npx skills add https://github.com/agents365-ai/365-skills --skill video-podcast-maker in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/video-podcast-maker/ (personal) or .claude/skills/video-podcast-maker/ (project).

Which AI agents can use video-podcast-maker?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is video-podcast-maker safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains video-podcast-maker?

It is published by agents365-ai in agents365-ai/365-skills. It has 2,710 recorded installs.

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