Video Production
speechlab0210/video-production-skill
AI educational video production pipeline. An agent skill from speechlab0210/video-production-skill.
Assemble a multi-scene GRWM beauty-demo ad from a config — a locked-identity creator applies ~5 products step by step while a SEPARATE ElevenLabs voiceover narrates and every scene cut is snapped to…
Install Render Glassy Matte Grwm
$ npx skills add gooseworks-ai/goose-skills --skill render-glassy-matte-grwm -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install gooseworks-ai/goose-skills render-glassy-matte-grwm --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-glassy-matte-grwm .claude/skills/render-glassy-matte-grwm && 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-glassy-matte-grwm" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-glassy-matte-grwm into .claude/skills/render-glassy-matte-grwm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-glassy-matte-grwm", 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-glassy-matte-grwmType 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-glassy-matte-grwm -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install gooseworks-ai/goose-skills render-glassy-matte-grwm --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-glassy-matte-grwm .agents/skills/render-glassy-matte-grwm && 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-glassy-matte-grwm" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-glassy-matte-grwm into .agents/skills/render-glassy-matte-grwm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-glassy-matte-grwm", 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-glassy-matte-grwm -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install gooseworks-ai/goose-skills render-glassy-matte-grwm --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-glassy-matte-grwm .cursor/skills/render-glassy-matte-grwm && 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-glassy-matte-grwm" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-glassy-matte-grwm into .cursor/skills/render-glassy-matte-grwm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-glassy-matte-grwm", 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-glassy-matte-grwm--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-glassy-matte-grwm -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install gooseworks-ai/goose-skills render-glassy-matte-grwm --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-glassy-matte-grwm .gemini/skills/render-glassy-matte-grwm && 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-glassy-matte-grwm" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-glassy-matte-grwm into .gemini/skills/render-glassy-matte-grwm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-glassy-matte-grwm", 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-glassy-matte-grwmInstalls 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-glassy-matte-grwm -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-glassy-matte-grwm .github/skills/render-glassy-matte-grwm && 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-glassy-matte-grwm" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-glassy-matte-grwm into .github/skills/render-glassy-matte-grwm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-glassy-matte-grwm", 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-glassy-matte-grwm -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-glassy-matte-grwm --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-glassy-matte-grwm .opencode/skills/render-glassy-matte-grwm && 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-glassy-matte-grwm" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-glassy-matte-grwm into .opencode/skills/render-glassy-matte-grwm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "render-glassy-matte-grwm", 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-glassy-matte-grwm- GitHub stars
- 1.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 795 words
- Files
- 6 (incl. scripts)
- Skills in repo
- 273
- Repo updated
- First seen
- Licence
- MIT
At a glance
Assemble a multi-scene GRWM beauty-demo ad from a config — a locked-identity creator applies ~5 products step by step while a SEPARATE ElevenLabs voiceover narrates and every scene cut is snapped to…
- The glassy-matte-grwm format
- SKILL.md covers Choices, Run and Contract (the free assembly)
- Tasks that involve Text to speech and voice
- Tasks that involve Speech recognition and synthesis
What it does
Render Glassy Matte Grwm is an agent skill from gooseworks-ai/goose-skills. Assemble a multi-scene GRWM beauty-demo ad from a config — a locked-identity creator applies ~5 products step by step while a SEPARATE ElevenLabs voiceover narrates and every scene cut is snapped to the VO's product-name word-starts (Whisper word-level timestamps), then ~5 Playwright product overlay cards (real PDP-verified taglines) are composited onto the master each on its product-NAME word-start, the SEPARATE VO is mixed on top of a ducked music bed at loudnorm I=-14, clean-white 3-words/cue captions are…
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts (for example `scripts/PIPELINE.md`, `scripts/README.md` and `scripts/config.example.json`).
It sits in Media & Creative, covering Text to speech and voice, Speech recognition and synthesis and Browser testing. It works with ElevenLabs and Playwright. 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 glassy-matte-grwm format
- Tasks that involve Text to speech and voice
- Tasks that involve Speech recognition and synthesis
Example prompts
- “/render-glassy-matte-grwm”
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 3 files in scripts/, 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 Glassy Matte Grwm loads about 1.6k tokens when it runs. Until then it costs about 236 tokens; SKILL.md has 795 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). 795 words, ~1,607 tokens.
Download SKILL.mdSave it as
.claude/skills/render-glassy-matte-grwm/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.- name
- render-glassy-matte-grwm
- description
- Assemble a multi-scene GRWM beauty-demo ad from a config — a locked-identity creator applies ~5 products step by step while a SEPARATE ElevenLabs voiceover narrates and every scene cut is snapped to the VO's product-name word-starts (Whisper word-level timestamps), then ~5 Playwright product overlay cards (real PDP-verified taglines) are composited onto the master each on its product-NAME word-start, the SEPARATE VO is mixed on top of a ducked music bed at loudnorm I=-14, clean-white 3-words/cue captions are burned, and the video closes on a flat-lay end card. This is the FREE deterministic assembly stage (re-cut to the VO word-starts, hard-concat, Playwright card render + card composite, VO plus music mix, caption burn, flat-lay end card); the VO, scene clips, product cutouts, and music come from create-music-elevenlabs / create-image-gpt-image-fal / create-video-fal. Use for the glassy-matte-grwm format.
- status
- active
render-glassy-matte-grwm
Assemble a multi-scene GRWM beauty-demo ad from a config — a locked-identity creator applies ~5 makeup/skincare products step by step in a chosen setting, a separate ElevenLabs voiceover narrates the routine, and every scene cut is snapped to the VO's product-name word-starts, with ~5 Playwright product overlay cards on the product-name beats, a ducked music bed, burned captions, and a flat-lay end card. This capability is the FREE, deterministic assembly — the Whisper-driven re-cut + hard-concat, the Playwright card render + card composite, the VO + music mix, the caption burn, and the flat-lay end card.
This is the multi-scene beauty demo, distinct from the single-take apparel outfit-reveal
(ugc-grwm, one Seedance reference-to-video call with native lip-sync and minimal post). Here the
timeline is driven by a SEPARATE VO and the scenes are re-cut to its word-starts.
scripts/config.example.json is the worked example (DIBS Beauty "5-Step Glassy Matte Routine",
~32s 1080×1920 9:16, 12 VO-snapped cuts + 5 product cards); scripts/PIPELINE.md maps every
config block to its source step and scripts/README.md documents the free assembly.
Choices
The creative calls come from the recipe's choices, asked of the user before any paid step. The
demo's picks are examples, never defaults. This capability only assembles what those choices
produced; it hardcodes none of them.
- creator — who does the routine (
assets.creator_anchor, the look in the scene beats). The demo used a young woman. - voice — the VO voice (
vo.voice_id/vo.voice_name). The demo used ElevenLabs Karri. - setting — where the routine happens (
assets.vanity_world). The demo used a sage-green vanity. - tone — how the VO talks (
vo.script,vo.style). The demo was upbeat and friendly. - music — the bed under the VO (
music.prompt; "none" = VO only, skip the music mix). The demo used a warm acoustic bed.
Card colours come from palette (the brand kit), not the demo's cream + pink.
Run
This is the FREE, deterministic assembly stage — it spends nothing. The paid inputs are
separate capabilities — the SEPARATE narration VO (create-music-elevenlabs, or a user-supplied
mp3; word-level Whisper timestamps set the timeline), ~7 Seedance scene clips one per product step
(create-video-fal), the ~5 white-bg product cutouts + the flat-lay end-card still
(create-image-gpt-image-fal), and the ducked music bed. Given the VO + .words.json + one clip
per step + the ~5 product cutouts + the music bed, render-glassy-matte-grwm re-cuts each clip to
its VO word-start window, hard-concats on the cut, renders + composites the product cards on the
product-name beats, mixes the VO over the ducked music, burns the captions, and appends the
flat-lay end card → the master. Re-cuts reuse the existing VO / clips / cutouts and cost $0.
Show full SKILL.md (382 more words)Show less
Contract (the free assembly)
- The SEPARATE VO drives the timeline — Whisper it first. The narration is a separate track (not a native take). Its word-level timestamps set every cut; the atempo'd VO ends shorter than the plan expects (a 1.15× VO landed ~27.5s), so time every window to the word-starts, never to a pre-planned grid.
- Scene cuts snap to the "step N" word-start; cards snap to the product-NAME word-start. Cut to the next product when its step is announced; the card animates in ~1s later when the NAME is spoken. Both happen. ~12 cuts over ~32s (cuts/10s ≈ 3.75).
- Hard-concat with a re-encode. Hard cuts on the VO word-starts, no dissolves; re-encode the
concat
-c:v libx264 -crf 20—-c copycorrupts the duration when zoompan/PNG clips are in the chain. - Product cards — Playwright, real cutout, PDP-verified tagline. Playwright renders the card
template at 2× scale (real white-bg cutout thumb + name + PDP tagline). The cutout must match the
REAL product, not the Seedance scene's hallucinated barrel; the tagline is verified against the
brand PDP (AI flat-lays hallucinate sublines). Composite each card onto the master snapped to its
product-NAME word-start, 1s fade-in, held until the next product is named. PNG overlay inputs
need
-loop 1 -t <dur>— without it the PNG emits one frame at t=0 and the fade/enable filters silently no-op (cards go invisible). - VO leads the ducked music bed. Mix the SEPARATE VO on top of the ducked music (the VO is the
lead),
loudnorm I=-14. Whenchoices.musicis "none", loudnorm the VO alone. If the host ffmpeg lacks a filter, apad/atrim to length before the mix. - Captions — clean-white, override the preset. Clean-white captions from the VO's Whisper
words, overridden to 3 words/cue, ~3.0% font, ~20% margin, NO pill, NO shadow (the default
5-words/4.5%/18% reads too dense). Burn last. If the host ffmpeg lacks libass, render the cues as
timed PIL PNG overlays composited with ffmpeg
overlay=…:enable='between(t,st,en)'at the same placement. - Flat-lay end card. Append the flat-lay still (ken-burns hold ~4s) — a gpt-image-2 flat-lay of the ~5 products; do NOT trust its AI-rendered sublines for the card taglines.
- FFmpeg composite, deterministic, FREE. Re-cut, hard-concat, render + composite the cards, mix the VO over the ducked music, burn the captions, append the end card → a 1080×1920 30fps h264+aac master (~32s). No paid calls, no keys.
© 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 5 other files (scripts) in skills/ads/capabilities/render-glassy-matte-grwm of gooseworks-ai/goose-skills.
- SKILL.md
- scripts/PIPELINE.md
- scripts/README.md
- scripts/config.example.json
- skill.meta.json
- tests/smoke-test.md
Open the folder on GitHubat commit c650c6d
Compare with similar skills
Render Glassy Matte Grwm 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 Glassy Matte Grwm this skillgooseworks-ai/goose-skills | 1.2k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Video Productionspeechlab0210/video-production-skill | 105 | — | ~4.1k | Automated safety check: Notes | MIT | |
| Local AI Useamd/skills | 408 | — | ~5k | Automated safety check: Notes | MIT | |
| Speech To Texttadaspetra/loop | 296 | 2 repos | ~2k | Automated safety check: Pass | MIT | |
| Whiteboard Videotrustfuture/simon-skills | 382 | — | ~1.8k | Automated safety check: Notes | MIT | |
| Bailian Media Generationmodelstudioai/cli | 542 | — | ~2k | Automated safety check: Pass | Apache-2.0 |
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Questions about Render Glassy Matte Grwm
What does Render Glassy Matte Grwm do?
Assemble a multi-scene GRWM beauty-demo ad from a config — a locked-identity creator applies ~5 products step by step while a SEPARATE ElevenLabs voiceover narrates and every scene cut is snapped to…. Render Glassy Matte Grwm is an agent skill from gooseworks-ai/goose-skills.
When should I use Render Glassy Matte Grwm?
Render Glassy Matte Grwm fits situations like: the glassy-matte-grwm format; tasks that involve Text to speech and voice; tasks that involve Speech recognition and synthesis.
How do I install Render Glassy Matte Grwm in Claude Code?
Run `npx skills add gooseworks-ai/goose-skills --skill render-glassy-matte-grwm -a claude-code`. Or copy the skill folder (skills/ads/capabilities/render-glassy-matte-grwm in gooseworks-ai/goose-skills) into .claude/skills/render-glassy-matte-grwm in your project. Claude Code loads it when a task matches its description.
How do I install Render Glassy Matte Grwm in Codex?
Run `npx skills add gooseworks-ai/goose-skills --skill render-glassy-matte-grwm -a codex`. Or copy the skill folder (skills/ads/capabilities/render-glassy-matte-grwm in gooseworks-ai/goose-skills) into .agents/skills/render-glassy-matte-grwm in your project. Codex loads it when a task matches its description.
Can I use Render Glassy Matte Grwm 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-glassy-matte-grwm -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-glassy-matte-grwm, .gemini/skills/render-glassy-matte-grwm, .github/skills/render-glassy-matte-grwm and .opencode/skills/render-glassy-matte-grwm in your project.
What does Render Glassy Matte Grwm need to run?
SKILL.md names no scripts, command-line tools or credentials: Render Glassy Matte Grwm is instructions for the agent only.
Does Render Glassy Matte Grwm 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 Glassy Matte Grwm 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 Glassy Matte Grwm use?
Render Glassy Matte Grwm 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 Glassy Matte Grwm use?
About 1.6k tokens (SKILL.md is roughly 6.4k 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 Glassy Matte Grwm?
Skills that share tags, products or a category with Render Glassy Matte Grwm: Video Production (speechlab0210/video-production-skill, 105 stars), Local AI Use (amd/skills, 408 stars), Speech To Text (tadaspetra/loop, 296 stars) and Whiteboard Video (trustfuture/simon-skills, 382 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Render Glassy Matte Grwm?
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.