Video Understand
calesthio/OpenMontage
Understand video content locally using ffmpeg frame extraction and Whisper transcription.
Assemble a short-form 'vignette' ad from clean product cutouts composited over a kinetic background video — birefnet cutout, then a cold-open text card + product carousel + annotated specimen-sheet…
Install Render Vignette
$ npx skills add gooseworks-ai/goose-skills --skill render-vignette -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install gooseworks-ai/goose-skills render-vignette --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ads/capabilities/render-vignette .claude/skills/render-vignette && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "render-vignette" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-vignette into .claude/skills/render-vignette/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-vignette", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-vignetteType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add gooseworks-ai/goose-skills --skill render-vignette -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install gooseworks-ai/goose-skills render-vignette --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ads/capabilities/render-vignette .agents/skills/render-vignette && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "render-vignette" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-vignette into .agents/skills/render-vignette/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-vignette", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gooseworks-ai/goose-skills --skill render-vignette -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install gooseworks-ai/goose-skills render-vignette --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ads/capabilities/render-vignette .cursor/skills/render-vignette && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "render-vignette" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-vignette into .cursor/skills/render-vignette/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-vignette", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/gooseworks-ai/goose-skills.git --path skills/ads/capabilities/render-vignette--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add gooseworks-ai/goose-skills --skill render-vignette -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install gooseworks-ai/goose-skills render-vignette --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ads/capabilities/render-vignette .gemini/skills/render-vignette && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "render-vignette" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-vignette into .gemini/skills/render-vignette/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-vignette", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install gooseworks-ai/goose-skills render-vignetteInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add gooseworks-ai/goose-skills --skill render-vignette -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ads/capabilities/render-vignette .github/skills/render-vignette && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "render-vignette" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-vignette into .github/skills/render-vignette/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-vignette", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gooseworks-ai/goose-skills --skill render-vignette -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install gooseworks-ai/goose-skills render-vignette --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ads/capabilities/render-vignette .opencode/skills/render-vignette && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "render-vignette" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-vignette into .opencode/skills/render-vignette/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-vignette", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
render-vignette- GitHub stars
- 1.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 624 words
- Files
- 7 (incl. scripts)
- Skills in repo
- 273
- Repo updated
- First seen
- Licence
- MIT
At a glance
Assemble a short-form 'vignette' ad from clean product cutouts composited over a kinetic background video — birefnet cutout, then a cold-open text card + product carousel + annotated specimen-sheet…
- Works in 4 steps: strip_product_backgrounds.py — birefnet… → render_overlays.py — PIL + rsvg-convert… → composite_variants.py — one FFmpeg… → …
- The vignette format
- SKILL.md covers Run, Choices, Contract and Gaps / routing notes
- Runs Python scripts from its folder
What it does
Render Vignette is an agent skill from gooseworks-ai/goose-skills. Assemble a short-form 'vignette' ad from clean product cutouts composited over a kinetic background video — birefnet cutout, then a cold-open text card + product carousel + annotated specimen-sheet end card, plus loudnorm + separate-pass music mux. FREE assembly (PIL + rsvg + FFmpeg); the recipe supplies the config and gates the paid BG/cutout/music calls to their own capabilities. Use for the vignette format.
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts (for example `scripts/composite_variants.py`, `scripts/music_and_mux.py` and `scripts/render_overlays.py`).
It sits in Media & Creative, covering Video production. It works with FFmpeg. The repository describes itself as: Library of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping. The licence is MIT.
When your agent uses it
- The vignette format
- Tasks that involve Video production
Example prompts
- “vignette”
- “/render-vignette”
Requirements
- Python 3
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- strip_product_backgrounds.py — birefnet cutout of each PDP shot to clean hard-edge alpha (no halo/shadow).
- render_overlays.py — PIL + rsvg-convert render the cold-open card (cold_open_text in cold_open_font, dead-center) + the annotated…
- composite_variants.py — one FFmpeg filter_complex per BG variant: BG (palette-aware dim) → cold-open overlay → cutouts (width-anchored…
- music_and_mux.py — instrumental music bed from config.music.prompt → acompressor + loudnorm I=-18:TP=-2:LRA=9 → muxed into every variant…
What it can do on your machine
Read from SKILL.md and the folder at commit c650c6d. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 4 files in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Render Vignette loads about 1.3k tokens when it runs. Until then it costs about 107 tokens; SKILL.md has 624 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from gooseworks-ai/goose-skills at commit c650c6d, republished under its MIT licence (© gooseworks-ai). 624 words, ~1,308 tokens.
Download SKILL.mdSave it as
.claude/skills/render-vignette/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- render-vignette
- description
- Assemble a short-form 'vignette' ad from clean product cutouts composited over a kinetic background video — birefnet cutout, then a cold-open text card + product carousel + annotated specimen-sheet end card, plus loudnorm + separate-pass music mux. FREE assembly (PIL + rsvg + FFmpeg); the recipe supplies the config and gates the paid BG/cutout/music calls to their own capabilities. Use for the vignette format.
- status
- active
render-vignette
Assemble a short-form 'vignette' ad from clean product cutouts composited over a kinetic background video. Motion lives in the BG video; the product rides on top as a static cutout layer. Music-led, zero VO, sub-12s, loopable — it reads muted because the product label + on-screen copy carry the message. Defaults to the V-CARD structure: a cold-open text card → a product carousel under one shared BG → an annotated specimen-sheet end card.
Run
strip_product_backgrounds.py— birefnet cutout of each PDP shot to clean hard-edge alpha (no halo/shadow).render_overlays.py— PIL +rsvg-convertrender the cold-open card (cold_open_textincold_open_font, dead-center) + the annotated specimen-sheet end card (brand SVG logo +end_card.linesannotations) as transparent 1080x1920 PNGs. Text colour followsend_card.logo_variant. FREE.composite_variants.py— one FFmpegfilter_complexper BG variant: BG (palette-aware dim) → cold-open overlay → cutouts (width-anchored, vertically centeredy=(H-h)/2) → end card. h264 crf20 yuv420p +faststart 30fps. FREE.music_and_mux.py— instrumental music bed fromconfig.music.prompt→acompressor + loudnorm I=-18:TP=-2:LRA=9→ muxed into every variant in a SEPARATE pass with explicit-map 0:v:0 -map 1:a:0. The mux is FREE; the music generation is a paid call that in prod routes through create-music-elevenlabs.
Every script reads config.json (--config <path>, $VIGNETTE_CONFIG, <project>/config.json or scripts/config.json) and exits naming any missing required field — there are no built-in demo values.
Choices
The recipe asks the user these before any paid step; this atom only reads the result from config. The demo build's value is an example, never a default.
bg_motif— the kinetic background's subject. Arrives asbg_concepts[].brief(BG sourced upstream). Demo: chrome molecular swarm / black ink blooming in cream.bg_palette— the background's colour feel. Arrives asbg_concepts[].dim(heavy/light dim) +end_card.logo_variant(logo + text colour). Demo: cream with chrome + ink accents.music— the instrumental bed's feel. Arrives asmusic.prompt(no brand names — ElevenLabs rejects them). Demo: slow ambient minimal electronic ~90 BPM.
Show full SKILL.md (328 more words)Show less
Contract
- FREE assembly: birefnet cutout (see gap below) + PIL/rsvg overlays + FFmpeg composite + mux. No AI-rendered text; the product art/labels and on-screen copy are real, never invented.
- The template recipe (DB) supplies the per-brand config (products, cold-open text, end-card lines, BG concept, beat timing). This capability is the generic assembler.
- Craft rules preserved from the source molecule:
- Cutouts stripped clean (no halo/shadow), height-anchored at vertical-center (
y=(H-h)/2) so mixed-shape SKUs share one visual mid-line — never bottom-anchor (squat jars jump). For 9:16 scale by WIDTH (~75% tall bottles, ~65% squat jars). - Palette-aware BG dim: high-contrast/chrome BG → push saturation DOWN hard (
saturation=0.50); naturally-contrasty BG → lighter dim (saturation=0.85). - End card = annotated specimen-sheet (EST year + rule + wordmark + rule + ingredient + positioning + claim), never a bare logo. Use the WHITE logo variant on dark BGs, cream on light.
- Music-led, NO VO — instrumental only (VO/lyrics would fight the cold-open + end-card text). Loudnorm before the mux.
- Mux is a SEPARATE FFmpeg pass with explicit
-map 0:v:0 -map 1:a:0(single-pass composite+mux silently ships 1 kbps garbage audio).
- Cutouts stripped clean (no halo/shadow), height-anchored at vertical-center (
Gaps / routing notes
- birefnet is a paid FAL model, not free.
strip_product_backgrounds.pycallsfal-ai/birefnet/v2directly via afal_helpersshim (sys.path.insertinto a shared atoms dir +from fal_helpers import ...). It is bundled here because the cutout is an intrinsic assembly step, but in prod the birefnet cutout should route through create-image-fal (the fal-proxy capability that bills the Ads agent) rather than hittingfal.rundirectly. Treat the direct-fal path as a gap to close; the recipe gates the cutout togooseworks fetch create-image-fal. - Background sourcing is not in this capability. The kinetic BG is sourced upstream — PEXELS-FIRST (free stock, the key cost lever), falling back to T2V (create-video-fal) only when stock coverage fails — and dropped into
source/t2v-outputs/<slug>.mp4so the composite is source-agnostic. There is no Pexels fetcher bundled here; that lives in the recipe's playbook. music_and_mux.pyalso uses thefal_helpersshim for the ElevenLabs music generation; in prod that generation routes through create-music-elevenlabs, and only the loudnorm + separate-pass mux run locally as FREE assembly.
© gooseworks-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 6 other files (scripts) in skills/ads/capabilities/render-vignette of gooseworks-ai/goose-skills.
- SKILL.md
- scripts/composite_variants.py
- scripts/music_and_mux.py
- scripts/render_overlays.py
- scripts/strip_product_backgrounds.py
- skill.meta.json
- tests/smoke-test.md
Open the folder on GitHubat commit c650c6d
Compare with similar skills
Render Vignette next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Render Vignette this skillgooseworks-ai/goose-skills | 1.2k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Video Understandcalesthio/OpenMontage | 66k | — | ~841 | Automated safety check: Pass | AGPL-3.0 | |
| HyperFrames Video Entry Pointheygen-com/hyperframes | 60k | 3 repos | ~5.2k | Automated safety check: Pass | Apache-2.0 | |
| Video Shotseternityspring/reelbench-skills | 878 | 1 repos | ~1.8k | Automated safety check: Notes | Apache-2.0 | |
| Mobile Demo Film Editorsuperset-sh/superset | 15k | — | ~1.8k | Automated safety check: Pass | Custom licence | |
| Video Editcalesthio/OpenMontage | 66k | — | ~855 | Automated safety check: Notes | AGPL-3.0 |
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Related
Works with
Categories
Questions about Render Vignette
What does Render Vignette do?
Assemble a short-form 'vignette' ad from clean product cutouts composited over a kinetic background video — birefnet cutout, then a cold-open text card + product carousel + annotated specimen-sheet…. Render Vignette is an agent skill from gooseworks-ai/goose-skills. Assemble a short-form 'vignette' ad from clean product cutouts composited over a kinetic background video — birefnet cutout, then a cold-open text card + product carousel + annotated specimen-sheet end card, plus loudnorm + separate-pass music mux.
When should I use Render Vignette?
Render Vignette fits situations like: the vignette format; tasks that involve Video production.
How do I install Render Vignette in Claude Code?
Run `npx skills add gooseworks-ai/goose-skills --skill render-vignette -a claude-code`. Or copy the skill folder (skills/ads/capabilities/render-vignette in gooseworks-ai/goose-skills) into .claude/skills/render-vignette in your project. Claude Code loads it when a task matches its description.
How do I install Render Vignette in Codex?
Run `npx skills add gooseworks-ai/goose-skills --skill render-vignette -a codex`. Or copy the skill folder (skills/ads/capabilities/render-vignette in gooseworks-ai/goose-skills) into .agents/skills/render-vignette in your project. Codex loads it when a task matches its description.
Can I use Render Vignette in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add gooseworks-ai/goose-skills --skill render-vignette -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/render-vignette, .gemini/skills/render-vignette, .github/skills/render-vignette and .opencode/skills/render-vignette in your project.
What does Render Vignette need to run?
Going by SKILL.md and its folder, Render Vignette needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Render Vignette access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Render Vignette safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Render Vignette use?
Render Vignette is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Render Vignette use?
About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Render Vignette?
Skills that share tags, products or a category with Render Vignette: Video Understand (calesthio/OpenMontage, 66k stars), HyperFrames Video Entry Point (heygen-com/hyperframes, 60k stars), Video Shots (eternityspring/reelbench-skills, 878 stars) and Mobile Demo Film Editor (superset-sh/superset, 15k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Render Vignette?
gooseworks-ai (a GitHub organization) maintains it in gooseworks-ai/goose-skills, which has 1,240 GitHub stars. The repository holds 273 skills in this directory. The repository was last updated on October 8, 2026.
Source: gooseworks-ai/goose-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.