Goose Skills is a library of workflows and data APIs that lets coding agents handle growth and go-to-market work such as advertising, social media, content, SEO, lead generation, and customer research. It is intended for teams using Claude Code, Cursor, Codex, and similar agents. The catalogue entries are its reusable skills.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/gooseworks-ai/goose-skillsnpx agentmods add skills/gooseworks-ai/goose-skills/render-hand-swipe-flavor-listicleWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/gooseworks-ai/goose-skills/render-hand-swipe-flavor-listicle)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/render-hand-swipe-flavor-listicle"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-hand-swipe-flavor-listicle/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/render-hand-swipe-flavor-listicle"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-hand-swipe-flavor-listicle.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00172 | $0.03103 |
| Opus 5.5 | $0.00069 | $0.01241 |
| Sonnet 5.5 | $0.00034 | $0.00621 |
| Haiku 4.5 | $0.00017 | $0.00310 |
Grade A, and why
render-hand-swipe-flavor-listicle scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| Hand clip | The bundled clip (one woman's hand): `curl -fL -o hand-swipe-greenscreen.mp4 https://d2m0qbg34x1ii2.cloudfront.net/ads/samples/455dc125-e41c-46dc-9fa6-9ae125e9b6bf/media-hand-swipe-greenscreen.mp4` (also in How it starts
The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
render-hand-swipe-flavor-listicle
Render the hand-swipe-flavor-listicle format from a config: a short vertical (1080×1920, 30fps, ~7.5s) "N flavors of " listicle. Each flavor is a card — a flat, saturated color field + a persistent title + the brand's REAL product cutout with a soft contact shadow. Cards change by sliding right-to-left (a phone-feed scroll), while a real-looking hand sweeps at the bottom of the frame. Music-only, no VO.
This capability is the FREE, deterministic assembly ($0, no keys). It never generates or edits the product — the cutouts are composited as-is, so labels stay crisp. It needs four kinds of input, gathered first (see Getting the inputs): product cutouts, a title TTF, a green-screen hand clip, and (optionally) a music bed.
Run
S=/tmp/gooseworks-scripts/render-hand-swipe-flavor-listicle/scripts # after `gooseworks fetch render-hand-swipe-flavor-listicle`
python3 $S/build_hand_swipe_listicle.py config.json # writes config "output"
python3 $S/build_hand_swipe_listicle.py config.json --out final.mp4 # override the output
python3 $S/build_hand_swipe_listicle.py config.json --stills cards/ # one PNG per card, no video
python3 $S/build_hand_swipe_listicle.py config.json --work work/ # keep the intermediates in work/
Relative paths in config.json resolve against the config file's own folder.
Render --stills first: it is instant and shows the title, colors and cutouts before the full render.
Prereqs: python3 with Pillow, and ffmpeg + ffprobe on PATH. Nothing else.
Getting the inputs
| Input | Free route | Paid route (gated: confirm with the user first) |
|---|---|---|
| Product cutouts | The brand's transparent PNGs (PDP/press kit). | A brand-site photo is usually NOT a cutout. Remove its background with create-image-fal, model fal-ai/birefnet/v2 (see below). |
| Title TTF | Download a TTF matching choices.title_style (table below). |
— |
| Hand clip | The bundled clip (one woman's hand): curl -fL -o hand-swipe-greenscreen.mp4 https://d2m0qbg34x1ii2.cloudfront.net/ads/samples/455dc125-e41c-46dc-9fa6-9ae125e9b6bf/media-hand-swipe-greenscreen.mp4 (also in the recipe's config.hand.bundled_clip_url). |
A new clip via create-video-fal (see Making the hand clip). |
| Music bed | None ("music": null, a silent cut). |
create-music-elevenlabs (see Making the music bed). |
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday Changed · +1 lines 7ebef3bebeff
- 16d ago First seen · 166 lines · 172 tokens per session scan A e1132f0b8ba3
render-hand-swipe-flavor-listicle is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,254 stars, last pushed today), licensed MIT. It adds 172 tokens to every session and 3,103 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-02.
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