
chanktb/any2video
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Deep-video skill: analyze any input (GitHub repo / URL / article / text) into a 9:16 narrated video — Claude writes the plan + per-scene HTML, TTS-first timing, karaoke captions, real repo-footage...
概要
Turn — a GitHub repo, a URL, an article, or raw text — into a (Reels / Shorts / TikTok format). Unlike fixed-template video generators, an agent (Claude Code or Antigravity) does the deep extraction itself and writes the narrative plan, then assembles each scene by picking a template from a catalog and filling it with real data — a path, not free-hand HTML, so the safe-zones / brand bars / caption band are always correct. The toolbox measures the voiceover, , renders, and composes the final mp4. These are baked into the pipeline (learned from a teardown of several 9/10 repo-tour Shorts — see skill/references/reference-video-teardown.md): - — burned per scene, filling word-by-word with the voice, number-words accented. (lib/compose/subtitles.py) - — a genuine scrolling screen-capture of the live repo (file tree → README → screenshots) or an author profile, framed in a browser chrome bar with the real URL. An authenticity beat, not synthetic text. (lib/render/repo_footage.
README
以下は原文 README の抜粋です。原文を見る。
any2video
Turn any input — a GitHub repo, a URL, an article, or raw text — into a 9:16 vertical narrated video (Reels / Shorts / TikTok format).
Unlike fixed-template video generators, an agent (Claude Code or Antigravity) does
the deep extraction itself and writes the narrative plan, then assembles each scene by
picking a template from a catalog and filling it with real data — a guarded path,
not free-hand HTML, so the safe-zones / brand bars / caption band are always correct.
The toolbox measures the voiceover, gates every scene, renders, and composes the
final mp4.
What makes the output feel professional
These are baked into the pipeline (learned from a teardown of several 9/10
repo-tour Shorts — see skill/references/reference-video-teardown.md):
- Word-synced karaoke captions — burned per scene, filling word-by-word with
the voice, number-words accented. (
lib/compose/subtitles.py) - Real repo-footage scenes — a genuine scrolling screen-capture of the live
repo (file tree → README → screenshots) or an author profile, framed in a
browser chrome bar with the real URL. An authenticity beat, not synthetic text.
(
lib/render/repo_footage.py) - Beat-split reveals — list/bar items appear (and bars fill left→right) exactly as the narrator names them, not all at once.
- AV-sync by design — TTS is measured first; scenes are joined with a gap-hardcut so the picture never drifts ahead of the voice.
- Reads brand names right, shows them clean — the voice speaks tricky names phonetically (“README” → “ruýt my”, “any2video” → “en ni tu vi đeo”) while every on-screen surface (title, karaoke caption, post) keeps the exact spelling.
- Ducked background music — a bundled track sits ~−20 dB under the narration and swells in the gaps (on by default; random from the pool or pick one).
- Reads the actual source, not just the README — for a repo it clones and opens the entry point + core files, traces the real flow, and mines the non-obvious “weapon” and the honest caveat from the code. Every architecture/flow claim is cited to a file, not a marketing bullet, so the tour reflects what the repo does, not what its README claims.
- Template-driven scenes with 3-tier safe-zone enforcement for 9:16 — every scene is measured and gated before render (see below), so broken frames never ship.
How it works (pipeline)
input → 1. extract → 2. plan (+ narrative gate) → ✋ approve script → 3. TTS (measure)
→ 4. fill templates → 4.5 GATE every scene → ✋ approve stills → render → 5. compose → mp4
TTS runs before the visuals so every scene’s layout is sized to the real
audio duration (no drift). See skill/SKILL.md for the full agent spec.
Two human checkpoints (optional, via Telegram) keep waste out of the loop:
- Script — before TTS. You see each scene’s on-screen text **and the read-aloud
推奨ツール
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インストール
npx skillfish add chanktb/any2video