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
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add gooseworks-ai/goose-skills --skill render-3d-product-showcasegit clone --depth 1 https://github.com/gooseworks-ai/goose-skillsWrote 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-3d-product-showcase)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/render-3d-product-showcase"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-3d-product-showcase/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-3d-product-showcase"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-3d-product-showcase.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00159 | $0.01120 |
| Opus 5 | $0.00079 | $0.00560 |
| Sonnet 5 | $0.00032 | $0.00224 |
| Haiku 4.5 | $0.00016 | $0.00112 |
Grade A, and why
render-3d-product-showcase scanned grade A with 0 findings 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 13d ago.
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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
render-3d-product-showcase
Assemble a premium 3D product-showcase ad from a config: one real product floats centered
on a clean seamless brand-color backdrop and sells itself across four beats — an orbiting hero
rotation, a macro push-in on the surface detail, a physics reveal (exploded_view /
particle_disintegration / liquid_splash, or rotation_only), then a typographic brand
close. This capability is the FREE, deterministic assembly that stitches the delivered
beats into the master; it spends nothing.
scripts/config.example.json is the worked example (DIBS Beauty "Desert Island Duo", ~15s
720×1280 9:16); scripts/build_endcard.py + scripts/build_masters.py are the runnable free
assembly; scripts/PIPELINE.md maps every config block to its source step; scripts/README.md
documents the assembly.
Run
This is the FREE, deterministic assembly stage — it spends nothing. The paid inputs are
separate capabilities: Beats 1 & 2 (hero rotation + macro push-in) are create-video-fal
image-to-video seeded on a create-image-fal styled hero — a nano-banana restyle of the
brand's REAL product photo onto the seamless studio set, so the product geometry is real and
never AI-invented; Beat 3 (the physics reveal) is a Veo3 image-to-video seeded on Beat 1's last
frame (also create-video-fal); the one instrumental bed is create-music-elevenlabs. There
is no Higgsfield / Marketing Studio in this format — everything paid runs through the
fal-proxy / elevenlabs-proxy so it bills the Ads agent.
Given those beats + the brand wordmark, this capability:
build_endcard.py --bg beat1_last_frame.png --headline "…" --wordmark <wordmark> --out endcard.png— the deterministic Beat-4 hyperframe (Playwright 1080×1920 → ffmpeg-scale to 720×1280).build_masters.py --config config.json --clips working/clips --endcard endcard.png --music music.mp3 --out master.mp4— trims each beat to its window, normalizes to the brand canvas, hard-concats, mixes the bed.
What ships with it
8 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.
- 13d ago First seen · 60 lines · 159 tokens per session scan A 4289a5761872
render-3d-product-showcase is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 159 tokens to every session and 1,120 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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