Guizang Social Cards
op7418/guizang-social-card-skill
Produces social card sets for Xiaohongshu and WeChat: carousels, Live Photo motion cards and puzzle layouts, and WeChat cover pairs, rendered from single-file HTML.
Watch a brand's own product footage (screen recording, product film), pick the moment that proves each line with the user, and render those picks as a product layer — free, local.
$ npx skills add gooseworks-ai/goose-skills --skill footage-cutlist -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install gooseworks-ai/goose-skills footage-cutlist --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/footage-cutlist .claude/skills/footage-cutlist && 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 "footage-cutlist" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/footage-cutlist into .claude/skills/footage-cutlist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "footage-cutlist", 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/footage-cutlistType 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 footage-cutlist -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install gooseworks-ai/goose-skills footage-cutlist --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/footage-cutlist .agents/skills/footage-cutlist && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "footage-cutlist" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/footage-cutlist into .agents/skills/footage-cutlist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "footage-cutlist", 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 footage-cutlist -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install gooseworks-ai/goose-skills footage-cutlist --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/footage-cutlist .cursor/skills/footage-cutlist && 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 "footage-cutlist" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/footage-cutlist into .cursor/skills/footage-cutlist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "footage-cutlist", 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/footage-cutlist--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 footage-cutlist -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install gooseworks-ai/goose-skills footage-cutlist --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/footage-cutlist .gemini/skills/footage-cutlist && 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 "footage-cutlist" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/footage-cutlist into .gemini/skills/footage-cutlist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "footage-cutlist", 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 footage-cutlistInstalls 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 footage-cutlist -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/footage-cutlist .github/skills/footage-cutlist && 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 "footage-cutlist" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/footage-cutlist into .github/skills/footage-cutlist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "footage-cutlist", 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 footage-cutlist -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 footage-cutlist --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/footage-cutlist .opencode/skills/footage-cutlist && 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 "footage-cutlist" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/footage-cutlist into .opencode/skills/footage-cutlist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "footage-cutlist", 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.
footage-cutlistWatch a brand's own product footage (screen recording, product film), pick the moment that proves each line with the user, and render those picks as a product layer — free, local.
Footage Cutlist is an agent skill from gooseworks-ai/goose-skills. Watch a brand's own product footage (screen recording, product film), pick the moment that proves each line with the user, and render those picks as a product layer — free, local. survey.py turns footage into timestamped contact sheets + scene cuts + motion so the agent can actually look at it; the agent writes a cut list (beat → source window + framing); preview.py draws it as a review sheet the user corrects round by round; cut.py renders the approved list into a silent 1080x1920 layer with the creator's area…
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including scripts (for example `scripts/_common.py`, `scripts/cut.py` and `scripts/cutlist.py`).
It sits in Media & Creative. 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.
9 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit c650c6d. It shows what the files ask for, not the result of running them.
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.
Ships 7 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
pythonFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Footage Cutlist loads about 2k tokens when it runs. Until then it costs about 207 tokens; SKILL.md has 1,003 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.
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.
The full file from gooseworks-ai/goose-skills at commit c650c6d, republished under its MIT licence (© gooseworks-ai). 1,003 words, ~1,951 tokens.
.claude/skills/footage-cutlist/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.Picking which moment of a customer's footage plays under which line is a judgement, not a formula. A position map ("beat 3 is 40% through the reel, so take the footage 40% through") was measured up to 5.7s off a person's picks on a reference build. So this capability does the free, mechanical parts and leaves the decision to the agent and the user:
| Step | Script | Who decides |
|---|---|---|
| Look at the footage | survey.py | nobody; it just shows it |
| Choose a window per line | the agent writes cutlist.json | agent, then the user |
| Show the choices | preview.py | the user corrects them |
| Render the approved choices | cut.py | nobody |
All free. ffmpeg + Pillow + numpy only.
python survey.py --video footage.mp4 --out work/survey # whole clip, ~1 frame/s
python survey.py --video footage.mp4 --out work/s-12 --from 12 --to 18 --every 0.25 --frames
python preview.py --cutlist work/cutlist.json --out work/review.png
python cut.py --cutlist work/cutlist.json --out work/layer.mp4 [--draft]survey.json lists cuts (scene changes), motion (change per second) and still
(runs of 1.5s+ with nothing moving: a dead screen reads as a frozen video). Read the
sheets; open a single frame-*.png (from --frames) when you need to read small UI text.
{
"size": [1080, 1920], "fps": 30, "seam": 768, "creator_side": "bottom", "bg": "auto",
"sources": {"demo": "footage/demo.mp4"},
"beats": [
{"id": "b1", "start": 0.0, "end": 3.1, "state": "creator", "vo": "..."},
{"id": "b2", "start": 3.1, "end": 7.4, "state": "split", "vo": "...",
"source": "demo", "in": 12.0, "fit": "width", "why": "the brand kit fills in at 13.4s"}
]
}state: creator (creator full frame), split (footage in the product zone, creator in
the other), product (footage full frame).in is where the window starts in the source; out defaults to in + slot (1.0x). A
window may play between 0.5x and 2x; it is never looped or frozen to fill a slot.fit: width (whole frame, letterboxed; the default), cover (fill + crop around
focus), crop (a source box [x0,y0,x1,y1] in fractions, then fit by width).bg: auto samples the footage's own corner colour so the letterbox and the footage read
as one surface; blur; or #rrggbb.look: "screen": frame the footage as a screen filmed at close range (thin bezel, dark
room, faint moire, grain, slow handheld drift). crop picks the source region,
screen: {rot, keystone, fill, fit, drift} the geometry, mask boxes are blurred in the
source (an email, a customer name). Inserts over a creator: keystone ~0.007,
rot within ±1°. Walkthroughs: keystone ~0.024, rot -1.5..0, fill ~0.80. Never
bigger angles and never alternate them between beats (read as a wonky camera).transition: {"dissolve_frames": 7} (top level): cross-dissolve every beat into the next.
A hard cut between two screens reads as an edit; 6-7 frames reads as the camera moving.look: "screen" so the drift keeps it alive.why: one line on what the window shows. It is printed on the review sheet so the user
can see the reasoning, and it makes the agent say what it saw.Beats must tile the timeline from 0 with no gaps. cut.py refuses a list that does not.
--every 0.25 and
look at every frame. A click, a page load or a half-typed field lives between the
samples, and it is exactly what a user then points out ("you didn't look at the video
properly").why.fit: width; use crop only to isolate a small
subject, and check the review sheet for cut-off text.still run reads as the video having stopped.
Start it where something moves, or shorten it.fit: width and let the room fill.mask it.cut.py warns when two beats overlap in the same source: it
reads as a loop.align_beats.py). Re-run preview.py + cut.py on the aligned list and look again.Expect several rounds. Each round:
review.png (and a --draft layer if they want to see motion).Picking is free, so take as many rounds as the user needs. Never spend on the creator until the user has approved the cut list.
A real product photo can use look: "photo". This is a dedicated contain/pan/zoom treatment without a screen bezel. photo accepts start/end scale (0.85–1.0), start/end pan pairs (-1–1), a normalized content box, and normalized protected source rectangles. An optional crop must contain every protected product/text rectangle. The selected region remains visible throughout motion. Use photo.box to reserve space above/below the seam for a qualification. Review first/middle/last frames; preview and render share the photo framing function. Existing plain stills and screen looks remain supported.
Before showing the cutlist, generate a footprint with caption-burn's bundled footprint.py, using the final style, anchor and font. Pass that JSON to preview's caption-footprint option. The amber band is the union of the actual rendered caption groups for that beat. Rebuild it after copy/timing/style changes. If it covers qualifying text, adjust photo.box, crop or layout, then inspect the final captioned video. Do not reduce or hide the qualification to make the claim fit.
© 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
SKILL.md and 9 other files (scripts) in skills/ads/capabilities/footage-cutlist of gooseworks-ai/goose-skills.
Open the folder on GitHubat commit c650c6d
Footage Cutlist 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 |
|---|---|---|---|---|---|---|
| Footage Cutlist this skillgooseworks-ai/goose-skills | 1.2k | — | ~2k | Automated safety check: Pass | MIT | |
| Guizang Social Cardsop7418/guizang-social-card-skill | 7.4k | 1 repos | ~7.8k | Automated safety check: Pass | AGPL-3.0 | |
| Weekly Changelog Videoheygen-com/hyperframes | 60k | — | ~3.3k | Automated safety check: Pass | Apache-2.0 | |
| Anthropic Brand Stylinganthropics/skills | 180k | 30 repos | ~559 | Automated safety check: Pass | Apache-2.0 | |
| MoneyPrinterTurbo Video Generatorharry0703/MoneyPrinterTurbo | 130k | — | ~2.1k | Automated safety check: Warn | MIT | |
| HyperFrames Media Useheygen-com/hyperframes | 60k | — | ~2.4k | Automated safety check: Pass | Apache-2.0 |
op7418/guizang-social-card-skill
Produces social card sets for Xiaohongshu and WeChat: carousels, Live Photo motion cards and puzzle layouts, and WeChat cover pairs, rendered from single-file HTML.
heygen-com/hyperframes
Turns a weekly changelog markdown file into a branded HyperFrames video with voiceover, animated mock-UI scenes and captions, using fonts, background and scripts bundled in the skill.
anthropics/skills
Applies Anthropic's brand colors and fonts to artifacts such as PowerPoint slides, using fixed hex values for text and accents, Poppins headings and Lora body text.
harry0703/MoneyPrinterTurbo
Installs and runs MoneyPrinterTurbo to turn a topic or script into a finished short video with voice-over, subtitles, stock footage and music.
heygen-com/hyperframes
Finds, generates and edits media for HyperFrames video projects: music, sound effects, images, icons, logos, voiceovers, captions and color grades.
EverettFish/holo-card-studio
Create collectible holographic foil cards and two-image lenticular flip cards with AI-generated full-color ukiyo-e and colored sumi-e anime artwork, layered Blender scenes, renders, GLB export, and…
gooseworks-ai/goose-skills
Scrape and search Reddit posts using Apify. An agent skill from gooseworks-ai/goose-skills.
gooseworks-ai/goose-skills
Generate or edit an image via any FAL image model (nano-banana edit, gpt-image, flux, ...), ROUTED THROUGH THE fal-proxy so it bills the Ads agent.
gooseworks-ai/goose-skills
Replace an existing video's opening with a supplied clip or free kinetic text hook while retaining and verifying every original body frame, audio, captions and ending.
gooseworks-ai/goose-skills
Scrape blog posts via RSS feeds (free, no API key) with Apify fallback for JS-heavy sites.
gooseworks-ai/goose-skills
Find leads by scraping engagers from a competitor's top LinkedIn posts.
gooseworks-ai/goose-skills
Assemble a ChatGPT chat-reveal video ad from a thread + timeline JSON — one continuous Playwright recording of a ChatGPT mobile chat (user types with the iOS keyboard up → taps send → keyboard…
Categories
Watch a brand's own product footage (screen recording, product film), pick the moment that proves each line with the user, and render those picks as a product layer — free, local. Footage Cutlist is an agent skill from gooseworks-ai/goose-skills. Watch a brand's own product footage (screen recording, product film), pick the moment that proves each line with the user, and render those picks as a product layer — free, local.
Footage Cutlist fits situations like: any format that shows real product footage beside; instead of a creator (split-screen.
Run `npx skills add gooseworks-ai/goose-skills --skill footage-cutlist -a claude-code`. Or copy the skill folder (skills/ads/capabilities/footage-cutlist in gooseworks-ai/goose-skills) into .claude/skills/footage-cutlist in your project. Claude Code loads it when a task matches its description.
Run `npx skills add gooseworks-ai/goose-skills --skill footage-cutlist -a codex`. Or copy the skill folder (skills/ads/capabilities/footage-cutlist in gooseworks-ai/goose-skills) into .agents/skills/footage-cutlist in your project. Codex loads it when a task matches its description.
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 footage-cutlist -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/footage-cutlist, .gemini/skills/footage-cutlist, .github/skills/footage-cutlist and .opencode/skills/footage-cutlist in your project.
Going by SKILL.md and its folder, Footage Cutlist needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
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.
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.
Footage Cutlist is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2k tokens (SKILL.md is roughly 7.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Footage Cutlist: Guizang Social Cards (op7418/guizang-social-card-skill, 7.4k stars), Weekly Changelog Video (heygen-com/hyperframes, 60k stars), Anthropic Brand Styling (anthropics/skills, 180k stars) and MoneyPrinterTurbo Video Generator (harry0703/MoneyPrinterTurbo, 130k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
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.