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-offer-adgit 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-offer-ad)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/render-offer-ad"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-offer-ad/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-offer-ad"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-offer-ad.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 78 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00235 | $0.02550 |
| Opus 5 | $0.00118 | $0.01275 |
| Sonnet 5 | $0.00047 | $0.00510 |
| Haiku 4.5 | $0.00023 | $0.00255 |
Grade A, and why
render-offer-ad 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 12d 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
render-offer-ad
The free, deterministic renderer for the motion-graphics-offer-ad format — the punchy ~12s vertical, music-only, direct-response offer ad built as a 4-beat kinetic -typography film: a HEADLINE slams in word-by-word → the real PRODUCT drops in → the CLAIM/proof lands → a CTA pill resolves. No character, no VO, no captions — the on-screen typeset text IS the message.
This is a bundled Remotion project (project/) driven by a thin Python driver. The
shipping master is 100% engine-rendered (springs + interpolate): backgrounds are
gradient divs off the brand_palette, props are inline SVG, and the ONLY composited
bitmap is the REAL product photo (objectFit:contain, never stretched). ALL
headline/claim/CTA/URL/wordmark text is typeset in the engine — never AI-rendered;
that is the format's credibility guard. Render cost is ~$0; the only paid step is an
optional music bed, gated upstream in the recipe to create-music-elevenlabs.
The whole ad is data: copy strings, product photo, palette, fonts, bpm, and beat
split all arrive as config.json and are bound to Remotion input props — nothing is
hardcoded in the scenes (the source run's Spoiled Child strings are generalised into
project/src/props.ts). Deterministic → iterate the cut for free.
The 4 beats (the spine)
- HEADLINE — primary-color radial ground;
headline_wordsslam in WORD-BY-WORD (slamIn, ~7-frame stagger, scale-overshoot + motion-blur smear, settling on the downbeat);subline+ an animated bobbing down-arrow drop in. - PRODUCT — light radial ground; the REAL product photo drops in (
dropIn) and idle-bobs (bob),objectFit:contain(never stretch); themotif_chippops in (popIn); optional GENERIC competitor shape + strike-through (wipe) — never a named competitor. - CLAIM — light radial ground; the
mechanism_propslides in from a frame edge (flyInovershoot, ~20% from the bottom) to add motion AND show the mechanism; the 3-line claim drops in staggered; product held bottom-right. - CTA — primary-color radial ground; the
wordmarkslams (slamIn); the CTA pill pops in as the motif-chip handoff resolving (popIn) with an arrow nudge; thecta_urlfades up.
What ships with it
19 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.
- project/.gitignore 143 B
- project/package.json 503 B
- project/public/.gitkeep 0 B
- project/remotion.config.ts 116 B runs code
- project/src/fonts.ts 1.4 KB runs code
- project/src/index.ts 108 B runs code
- project/src/lib/anim.ts 4.8 KB runs code
- project/src/Main.tsx 1.5 KB
- project/src/props.ts 4.1 KB runs code
- project/src/Root.tsx 1.0 KB
- project/src/scenes/Scene01.tsx 5.0 KB
- project/src/scenes/Scene02.tsx 4.9 KB
- project/src/scenes/Scene03.tsx 6.5 KB
- project/src/scenes/Scene04.tsx 3.5 KB
- project/tsconfig.json 293 B
- scripts/config.example.json 2.1 KB
- scripts/render.py 12 KB runs code
- skill.meta.json 307 B
- tests/smoke-test.md 4.9 KB
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.
- 12d ago First seen · 142 lines · 235 tokens per session scan A 8431e04b39f9
render-offer-ad is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 235 tokens to every session and 2,550 once invoked, about $0.0012 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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