| name | slides-to-video |
| description | Use when the user wants to turn prepared slides (PNG, PDF, or PPTX) into a narrated, captioned video in a chosen language and presenter role, using only free tools. A three-phase human-in-the-loop flow (analyze, draft transcript, render) gates rendering behind an explicit transcript approval. |
| metadata | {"short-description":"Narrated, captioned videos from prepared slides using free tools"} |
OpenCode Runtime Notes
This skill is installed as an OpenCode-native SKILL.md. For runtime-backed
helpers, prefer the shared ai-agents-skills runtime root and the
AAS_RUNTIME_ROOT override instead of assuming a Codex-specific runtime
path.
Slides to Video
Turn already-prepared slides into a narrated, captioned MP4 in a user-chosen
language and presenter role. Everything is free of charge and runs from a
dedicated Python virtualenv plus ffmpeg. Voice quality is maximized with a
language-aware TTS ladder; English and Vietnamese are first-class.
Windows Runtime Commands
On native Windows, use the managed Windows runner and the native runtime command
target. Set $runtime to the installed runtime root. Multi-agent installs usually use %LOCALAPPDATA%\ai-agents-skills\runtime.
$runtime = if ($env:AAS_RUNTIME_ROOT) { $env:AAS_RUNTIME_ROOT } else { "$env:LOCALAPPDATA\ai-agents-skills\runtime" }
& "$runtime\run_skill.bat" "skills/slides-to-video/run_slides_to_video.bat" <args>
& "$runtime\run_skill.bat" "skills/slides-to-video/run_slides_to_video.ps1" <args>
POSIX examples below use run_skill.sh and the .sh command target.
When to use
Use this skill when the user wants to:
- narrate a deck they already exported as high-resolution PNG (1920x1080 or
3840x2160), PDF, or PPTX
- produce a presentation/lecture video with a chosen voice, language, and role
(presenter, teacher, lecturer, narrator, pitch)
- add Tier-1 visual effects (Ken Burns, highlight, spotlight, laser pointer,
step reveal) on top of the slides
- generate synced captions (SRT + VTT), with Vietnamese diacritics handled
Do NOT use this for authoring math animations from scratch (handwritten
equations, equation morphing) -- that is the planned, separate slides-to-video
Manim extension. This skill consumes pre-made slides.
Free-tools and licensing posture
- TTS: edge-tts (online, best voice), Kokoro (offline, Apache-2.0), Piper
(offline, 30+ languages). XTTS-v2 is excluded (non-commercial license).
- Assembly:
ffmpeg is the one required system tool. Use an LGPL build; the
H.264 patent obligation applies to redistribution of output, not local use.
- Python packages run only in the dedicated venv; nothing is vendored.
Setup (one time, explicit)
Step 1 - install the SYSTEM tools with your OS package manager. ffmpeg/ffprobe
is the only hard requirement; espeak-ng is needed only for offline TTS
(Kokoro/Piper); a PPTX renderer is needed only for PPTX input. On Windows,
Microsoft PowerPoint from Microsoft Office is supported through COM automation,
so LibreOffice is not needed when Office is installed. On Linux/macOS, use
LibreOffice for PPTX input.
sudo apt-get update && sudo apt-get install -y ffmpeg espeak-ng libreoffice
sudo dnf install -y ffmpeg espeak-ng libreoffice
sudo pacman -S ffmpeg espeak-ng libreoffice
brew install ffmpeg espeak-ng && brew install --cask libreoffice
winget install Gyan.FFmpeg eSpeak-NG.eSpeak-NG
Step 2 - create the dedicated venv and check readiness. Once the skill is
installed into an agent home, use the managed runner:
bash "$AAS_RUNTIME_ROOT/run_skill.sh" skills/slides-to-video/run_slides_to_video.sh setup
bash "$AAS_RUNTIME_ROOT/run_skill.sh" skills/slides-to-video/run_slides_to_video.sh doctor
To try it straight from the repo before installing, call the script directly:
bash canonical/runtime/skills/slides-to-video/run_slides_to_video.sh setup
bash canonical/runtime/skills/slides-to-video/run_slides_to_video.sh doctor
setup creates ~/.local/share/slides-to-video-venv and installs requirements.
doctor prints a JSON report of exactly what is present or missing and never
installs anything. On Windows, doctor reports system_tools.powerpoint when
Microsoft PowerPoint is available for PPTX rendering.
The three-phase, human-in-the-loop flow
Rendering is impossible until the transcript is explicitly approved; editing the
transcript after approval re-blocks rendering (the approval is pinned to the
SHA-256 of transcript.json).
Phase 1 - Analyze. Ingest slides and record decisions.
... run_slides_to_video.sh analyze \
--input "/path/to/slides_dir_or_file" \
--work-dir "/path/to/deck_work" \
--language vi-VN --role teacher --engine-policy auto --resolution 1920x1080
Writes deck.json, config.json, and ordered frames under slides/.
For PNG-only input there is no embedded text, so seed each slide's narration by
reading the slide image (vision) before/while drafting.
Phase 2 - Draft transcript and iterate. Scaffold, then write the narration.
... run_slides_to_video.sh draft --work-dir "/path/to/deck_work"
This creates transcript.json (authoritative spoken text + per-slide effects)
and transcript.md (human-readable view). Edit transcript.json to write the
actual narration per slide, then regenerate the view and present it to the user.
For math decks, run verbalize to rewrite notation into speakable words
(e.g. x^2 -> "x squared" / "x binh phuong"); the user reviews the spoken form.
Iterate (edit specific slides, regenerate) until the user is satisfied.
Approve (explicit gate).
... run_slides_to_video.sh approve --work-dir "/path/to/deck_work"
Only do this on an explicit user "approve/render it". It pins the transcript SHA.
Phase 3 - Render.
... run_slides_to_video.sh render --work-dir "/path/to/deck_work"
Per slide: synthesize narration via the language-aware ladder, normalize to WAV,
measure the exact duration with ffprobe, build a clip of exactly that length
with any effects, then losslessly concatenate. Outputs video.mp4,
captions.srt/.vtt, and render_report.json. Refuses if not approved.
status --work-dir ... reports pipeline state at any time.
Languages
The core is language-agnostic. English and Vietnamese are tuned (math lexicon,
voices, fonts). Caption font selection prefers the lexicon's font hint, then
falls back to installed Vietnamese-capable fonts such as Be Vietnam Pro, Arial,
Calibri, Segoe UI, Tahoma, Times New Roman, or DejaVu Sans. Any other language
the engines cover is supported generically:
edge-tts serves ~70 locales online; Piper covers 30+ offline; Kokoro covers 9.
The ladder is language-aware -- e.g. Vietnamese never routes into Kokoro (which
has no Vietnamese voice); offline Vietnamese uses Piper vi_VN-vais1000-medium,
online uses edge-tts vi-VN-HoaiMyNeural/NamMinhNeural. To make another
language first-class, add s2v/languages/<lang>.json (voices + math lexicon)
and confirm a covering font; no code change.
Effects
Tier-1 effects operate on the rendered slide pixels (no authoring): ken_burns,
highlight, spotlight, laser, reveal. Specify them per slide in
transcript.json under each slide's effects list. See
references/effects.md.
Animated math interludes (Manim)
A slide's visual can be a pre-rendered video clip instead of a static image:
set clip_path on a slide in transcript.json, or insert one with add-interlude.
This is how a manim-math-animation clip is mixed into a narrated deck.
... run_slides_to_video.sh add-interlude --work-dir "/path/to/deck_work" \
--clip "/path/to/manim_clip.mp4" --after 0 \
--transcript "Completing the square gives a perfect square."
The clip becomes a new slide (inserted after the given index; slides are
reindexed and the deck/transcript stay 1:1). Narration is still synthesized by
the TTS ladder, so the Manim clip stays silent (one timing owner). The segment
runs to max(clip_duration, narration_duration): a shorter clip freezes its last
frame, shorter narration is padded with silence -- so the lossless concat stays
drift-free. add-interlude invalidates any prior approval, so re-approve
before render. See references/pipeline-and-sync.md.
References
references/pipeline-and-sync.md - duration-driven sync, the 1:1 pairing
contract, encoding settings, and the approval gate.references/effects.md - effect types and their parameters.references/languages-and-tts.md - the engine ladder, per-language data, and
spoken-math verbalization.references/design.md - architecture, scope, and the deferred Manim extension.
