html-explainer

An Agent Skill: give it a topic, get back a narrated explainer video with subtitles and covers.

Write scenes in HTML → deterministic frame-by-frame rendering → a real MP4. Everything runs locally; the core pipeline needs no API key and charges no per-render fee.

简体中文 · English

Three finished videos made with this skill — visuals, voiceover, subtitles and covers all produced by the pipeline, no manual post-production. Covers and other assets live in a separate demos repository; this repo stays text-only.

https://github.com/user-attachments/assets/912e6c2d-831f-43dd-a39f-57b749bb417d

HK innovative drugs · early session	A quant firm built an LLM
https://github.com/user-attachments/assets/8007843c-088d-457c-8550-81ec912e0add	https://github.com/user-attachments/assets/28949988-449b-4c4e-8d0f-6706af6f64ee

Follow the test accounts — watch the video stats in real time

Douyin · OnlyOneMoh	Profile · Moen	Douyin · Moen_xin

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What it is

html-explainer turns a topic into a narrated explainer video with burned-in subtitles and a progress bar, with the visuals written in HTML/CSS/GSAP.

It is an Agent Skill (SKILL.md + scripts/ + references/), following the Agent Skills convention, so Claude Code, OpenAI Codex, WorkBuddy, Cursor, Gemini CLI and others can load it directly. Underneath it is plain Python and Node scripts, so you can also run it by hand.

You say one sentence:

Make a 1-minute explainer video about why the sky is blue.

The skill then walks the agent through: research → script → voiceover → subtitles and beats → scene authoring in one of 23 styles → render → QC → covers.

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Install

One-line install (recommended)

Send this to your agent:

Install this Skill into my local environment: https://github.com/OneMoh/html-explainer.git
Put it in your skills directory and check/install the required runtime
(Python 3.9+ / Node 18+ / Chrome or Edge / ffmpeg)

It clones into the right directory, runs the environment check and installs whatever is missing. Then start a new session so the agent rescans its skills directory.

Manual install

The repository root is the skill directory (SKILL.md sits at the root), so clone it straight into your skills directory — there is no subdirectory to copy:

git clone https://github.com/OneMoh/html-explainer.git ~/.workbuddy/skills/html-explainer
bash ~/.workbuddy/skills/html-explainer/setup_env.sh --install

On Windows ~ is C:\Users\<you>.

Skills directory by agent

Agent	Personal (global)	Project (in-repo)
WorkBuddy	~/.workbuddy/skills/	<workspace>/.workbuddy/skills/
Claude Code	~/.claude/skills/	.claude/skills/
OpenAI Codex	~/.codex/skills/	.codex/skills/ or .agents/skills/
Gemini CLI	~/.gemini/skills/	.gemini/skills/ or .agents/skills/
Cursor	~/.cursor/skills/	.cursor/skills/
GitHub Copilot / VS Code	~/.copilot/skills/	.github/skills/
OpenCode	~/.config/opencode/skills/	.opencode/skills/
Windsurf	~/.windsurf/skills/	.windsurf/skills/
Others (common convention)	~/.agents/skills/	.agents/skills/

If unsure where to put it, prefer .agents/skills/ — most tools read it. (Claude Code is the exception and only reads .claude/skills/.)

Requirements

Item	Minimum	Notes
Python	3.9+	edge-tts==7.2.8 (pinned deliberately — v7 changed the boundary API), numpy, pillow, imageio-ffmpeg. The Volcano engine needs nothing extra (stdlib urllib only, no SDK)
Node.js	18+	Used by the renderer and the cover builder
Browser	Chrome or Edge	Auto-detected; playwright chromium (~115MB, one time) only if neither exists
ffmpeg	any version	Looked up on PATH; falls back to the static binary bundled with imageio-ffmpeg
Disk	~2GB per video	Frame PNGs are large; safe to delete after muxing

bash setup_env.sh only reports what is missing; --install installs it. No admin rights needed.

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Voice-over: two engines

Before the pipeline starts the agent asks which TTS you want, then lists candidate voices for you to pick from (or you can just hand it a voice ID):

	edge-tts	Volcano Engine TTS 2.0
What you do	nothing	paste an API Key once
Cost	free	billed per character
Voices	a set of built-in zh/en voices	Doubao 2.0 voice library, incl. voice cloning
Word timestamps	WordBoundary	sentence.words[]
Extra deps	edge-tts==7.2.8, imageio-ffmpeg	none — stdlib urllib only
When to pick it	default; works out of the box	when you want more natural prosody / better quality

Both engines emit an identical audio-manifest.json, so the timeline, the subtitles and the renderer all stay untouched — switching engines is a one-field change.

With Volcano, the only thing you touch

The first time it runs Volcano, the skill creates a tts.env and stops, then tells you to paste your API Key into it (console → Speech → API Key management). Say "done" and the agent tests the connection, confirms the voice, and carries on.

That step deliberately bypasses the chat window — the key is never sent to the agent, and the agent never needs to know it.

Built-in voices (full list in the official voice docs):

Male	Female
Yunzhou 2.0 (default) · Wennuan Ahu 2.0 · Jieshuo Xiaoming 2.0 · Cixing Jieshuo Nan 2.0 Xuanyi Jieshuo 2.0 · Guanggao Jieshuo 2.0 · Ruya Qingnian 2.0 · Shaonian Zixin 2.0 · Shenye Boke 2.0	Xiaohe 2.0 · Vivi 2.0 · Zhixing Cancan 2.0 Tianmei Taozi 2.0 · Linjia Nvhai 2.0 · Wenrou Shunv 2.0

If the built-in list is not enough, a voice ID from voice cloning works too.

Key discipline

The API Key lives only in tts.env, and only one interface package inside the skill reads it. The agent calls that package, so it neither gets nor needs the key value:

you (fill it in once) → tts.env (already gitignored)
                            ↓  only the interface package reads it
                     synthesis call  ← the agent calls this; never sees the key
                            ↓
                     Volcano Engine

• Never in the chat: ask the agent for key status; what comes back is a masked summary (ef90******86c8).
• Never in the repo: .gitignore covers tts.env / *.env / *.key / *.pem / secrets/; the repo self-check has a dedicated key-defence rule, itself proven by a negative test — a deliberately planted fake key gets caught.
• Never in logs: error messages are redacted — only the key value actually used and AKLT… tokens are scrubbed. Deliberately not a broad "any long string is a secret" rule, which would also erase the request IDs you need for support.
• Never in a distribution: packaging the skill excludes key files.
• Backstop (the real security boundary): if it leaks anyway, keep the blast radius small — use a sub-account with speech-synthesis-only permission, set usage alerts and quotas, and rotate the key.

Bluntly: the synthesis code runs on your machine, so the key is visible to that process at runtime — "the agent can never read it" is not achievable. What is guaranteed is not in the chat, not in the repo, not in the logs, not in the distribution, which shrinks a leak into one revocable incident.

Also don't store the key in an environment variable — many hosts dump the process environment straight into the session transcript.

Don't rename tts.env.example to tts.env and fill that in. It is the template meant to stay in the repo; renaming it leaves everyone else without one (the repo self-check reports it). Copy it, then fill the copy.

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Video project layout

Say one sentence and the agent walks the whole pipeline inside a video project directory; output lands in out/: slug.mp4, cover_169.png, cover_34.png, slug.srt, slug.vtt, plus qc_report.md and qc_sheet.jpg.

A video project looks like this:

my-video/
├── project.json      # slug, fps, size, voice, rate, scene order, chapters
├── narration.json    # [{ id, text }] — pipes "|" split subtitle blocks
├── theme.css         # every colour, as CSS variables
├── frames/           # one HTML per scene; <id>.beats.js is generated, never hand-edited
├── audio/  render/  research/  script/
└── out/              # MP4, covers, SRT/VTT, QC report

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Why not screen recording

Most "HTML to video" tools launch a browser, play the animation and record the screen. That breeds a whole class of intermittent bugs — the animation played before recording started, a web font loaded late so half the video used the wrong typeface, the first frames captured the pre-animation state.

html-explainer does not record. It seeks: position the GSAP timeline at that instant (tl.pause(t, false)), sync every CSS animation (document.getAnimations().currentTime), wait two animation frames, screenshot. Frame 1204 of one render is pixel-identical to frame 1204 of the next — so QC can point-sample, a single scene can be re-rendered alone, and a whole class of timing bugs becomes impossible.

The trade-off: every animation must be seekable. Wall-clock animation (setInterval, requestAnimationFrame counters, CSS transition entrances) cannot work and is rejected by lint_frames.py.

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Features

Beats anchored to narration	Scenes position animation by matching subtitle text (B('block text')), never by hardcoded frame numbers. Edit the script and the whole video re-times with zero scene-code changes.
Word-boundary subtitles	Timing comes from the TTS engine's character-level timestamps, never interpolated by character count — in Chinese two phrases of equal length can differ 3× in duration. WordBoundary for edge-tts, sentence.words[] for Volcano Engine.
Two voiceover engines	edge-tts (free, no key, default) or Volcano Engine TTS 2.0 (better quality, needs an API key). Both emit an identical manifest, so nothing downstream changes — switch with --provider.
The API key never reaches the agent or the repo	The Volcano key lives only in tts.env (gitignored) and only the interface package reads it — the agent calls tts_volcano.py and never needs the key. Errors are redacted, check_integrity.py enforces a secret guard, and packaging excludes key files.
Two-level clock	Frame length uses MP3 container duration (keeps A/V in sync); the final subtitle block ends on actual speech end.
23 visual styles	8 categories, each with its canvas, type scale, timeline and colour discipline recorded. No designing from a blank page.
Dual covers	Every video ships a 16:9 cover plus an independently re-laid-out 3:4 cover — not a crop. Cropping loses 57.8% of the width.
Pre-render audit + QC	lint_frames.py reports contract violations before you spend render time; qc_check.py checks loudness, drift and samples frames.
Structurally offline	GSAP vendored; browser auto-detected; ffmpeg falls back to the imageio-ffmpeg static binary; web fonts are banned by contract.

---

Pipeline

flowchart LR
    A["Topic"] --> B["Research<br/><i>every figure sourced</i>"]
    B --> C["narration.json<br/><i>pipes split subtitle blocks</i>"]
    C --> S["tts_setup.py<br/><i>ask engine · key · voice</i>"]
    S --> D["tts_build.py<br/><i>edge-tts / Volcano to MP3 + word boundaries</i>"]
    D --> E["timeline_build.py<br/><i>global axis + stitched track</i>"]
    E --> F["subs.py<br/><i>subs.json, srt/vtt, beats.js</i>"]
    F --> G["frames/*.html<br/><i>one scene per line, styled from the library</i>"]
    G --> H{"lint_frames.py<br/>eight contract rules"}
    H -->|fail| G
    H -->|pass| I["render_video.mjs<br/><i>seek per frame to PNG</i>"]
    I --> J["ffmpeg<br/><i>H.264 + AAC mux</i>"]
    J --> K[("out/slug.mp4")]
    I --> L["qc_check.py<br/><i>loudness, drift, contact sheet</i>"]
    K --> M["cover_build.mjs<br/><i>cover_169.png, cover_34.png</i>"]

    style K fill:#1f6feb,color:#fff
    style H fill:#8957e5,color:#fff
    style M fill:#238636,color:#fff

---

The B() beat system

subs.py emits one beats.js per scene, exposing each subtitle block by its source text, so scene animation can be anchored directly to the moment words are spoken:

tl.fromTo('.card',    { y: 60, autoAlpha: 0 }, { y: 0, autoAlpha: 1, duration: 0.7 }, B('right-hand card'));
tl.fromTo('.verdict', { scale: 0.8 },          { scale: 1, duration: 0.6 },        B('the verdict') + 0.2);

B('block text') is the moment those words start being spoken; Be('block text') is the moment they finish.

This is this project's own design, and it is the part that changes how the work feels: edit the narration once, re-run three commands, and every scene re-times itself. Compare with hardcoded frame numbers — one edited sentence means re-aligning the entire video by hand.

Fallbacks are forbidden. B('x') || 3.2 hides "beat not found" behind a stale number. A miss should fail the build — a mis-timed video is far worse than a failed build.

---

Visual style library

Do not design scenes from a blank page. 23 styles across 8 categories, each recording its canvas, type scale, timeline structure and colour discipline — full catalogue in references/style-catalog.md (Chinese).

It covers bold signal cards, luxurious minimal whitespace, NYT-grade data charts, Swiss grid, glitch art, film light leaks, fluid hero backgrounds, brand logo outros, VFX text cursors, 9:16 social formats, product promos and more.

Two classes, with very different adaptation costs:

• rich (12) — single file, pure CSS @keyframes. The seek renderer drives them with no changes; adaptation is three steps: swap web fonts for a system stack, lift bottom elements out of the subtitle band, drop in real content.
• gsap (11) — multiple compositions loaded from a CDN. Do not port the code. Take only the visual DNA and re-express it in CSS keyframes.

Rotate 2–4 styles per project. Eight scenes sharing one look reads as monotonous.

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Dual covers

Every video ships two covers that are siblings, not crops. Cropping 16:9 to 3:4 leaves 810px of 1920px — 57.8% of the width is gone, and any full-width headline gets sliced in half. So both share one visual DNA, but each is laid out again from scratch:

Element	16:9 (1920×1080)	3:4 (1440×1080)
Paradox visual	Right side, side by side	Top, stacked vertically
Hook	Bottom-left, two lines, ≥96px	Bottom, three lines, ≥120px
Max characters per line	7	5

new_project.py generates the templates for both sizes directly; output is 2× by default. Full rules and the pre-upload checklist: references/cover-guide.md (Chinese).

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Troubleshooting

Symptom	Cause	Fix
Every frame is a frozen first frame, no error	Timeline not registered on window.__tl; or page.evaluate received a string instead of a function literal (Playwright evaluates it once, so the body never runs)	Pass a real function literal
Video comes out 1280×720	viewport was passed to browser.launch() — it is a context-level option	Pass it to newPage()
Cover renders at 1×	Same trap, deviceScaleFactor twin	Pass to newPage() + screenshot({ scale: 'device' })
Numbers render but never move	The seek suppressed onUpdate callbacks	Renderer fixed (pause(t, false)); use a transform-based number reel in scenes
No such file or directory on Windows	Non-ASCII path — Windows ffmpeg reads UTF-8 as ANSI	Keep paths ASCII
Subtitles drift / land in the wrong place	TTS returned no word timestamps, so subs.py fell back to character-count interpolation (a single stderr warning)	Check whether tts_build printed ⚠ no word timestamps; switch to a supported voice (zh/en Doubao 2.0)
Volcano error resource ID is mismatched with speaker related resource	speaker got a display name instead of a voice ID; or a cloned voice paired with the preset resource ID	Use a built-in voice name/ID (the package resolves it); for cloned voices set VOLC_RESOURCE_ID=seed-icl-2.0
Volcano HTTP 401/403	Wrong key in tts.env, or the service is not enabled	Verify VOLC_API_KEY; check the masked status via tts_setup.py --status
Volcano network unreachable	The package bypasses the system proxy by default (China-mainland endpoint)	If you really need a proxy, set VOLC_PROXY=http://127.0.0.1:<port>
Subtitles sit one frame late after a re-run	A cache hit dropped the head-trim amount (historical bug, fixed)	Upgrade to v1.3.0+; the cache format now carries lead_cut_sec

references/lessons.md is the most valuable file in this repository. 56 numbered entries, each one a bug where "the video looked fine but was wrong" — including how it was misdiagnosed at first. Read it before debugging from scratch.

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Who this is for

Good fit: turning articles, docs or a topic into narrated video at scale; already using an AI coding agent and preferring to describe visuals in HTML rather than learn motion software; needing reproducible output; needing to run offline or refusing per-render fees.

Poor fit: live-action editing, talking-head footage, re-creating an existing video; wanting a drag-and-drop editor (scenes are code, deliberately); wanting React component animation as the authoring model — that is the domain of the reference project anything2explainer.

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Reference project ideas

html-explainer did not invent its methodology. It has two clear sources of ideas. Both are independent projects by different authors — not the same author as this one, and this repository neither bundles nor depends on any of their code at runtime. What was carried over is design specification and engineering experience.

• Vincentwei1021/anything2explainer (TypeScript / Remotion) — topic in, narrated explainer video out. What this project inherited from that line is the narration and A/V-sync methodology: word-boundary subtitles, the two-level clock, speech-rate calibration, and the QC criteria. Difference: it is Remotion plus React component animation; this project is HTML/CSS/GSAP plus deterministic seeking.

• nexu-io/html-video (Apache-2.0, by the Open Design team) — HTML to real MP4 on your own machine. What this project inherited from that line is the 23-style visual catalogue, transcribed from its template design specifications. Seven of those styles trace further back to MIT-licensed design work. Difference: it relies on real-time recording; this project seeks frame by frame, so output is reproducible.

This project's own parts: the deterministic seek renderer, B() beat anchoring, the dual-cover system, and the criteria in lint_frames.py / qc_check.py. Full attribution and the per-style mapping are in THIRD_PARTY_NOTICES.md (Chinese).

If you want React component animation or Studio-style visual collaboration, go straight to the two projects above. If you want to edit one sentence without re-aligning the whole video by hand, and you want frame-level reproducibility, use this one.

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Contributing

Issues and PRs are welcome. The most valuable contribution is a diagnosed silent failure added to references/lessons.md — write down how it first misled you, the evidence that proved the cause, the fix, and the general rule that follows. Please read CONTRIBUTING.md first (Chinese).

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Licence and acknowledgements

MIT © 2026 Moh

MIT covers the original code and documentation. Bundled third-party components and the derived style specifications remain under their own terms; GSAP is bundled under GreenSock's standard "no charge" licence. Full notices are in THIRD_PARTY_NOTICES.md (Chinese).