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 remix-graphic-ad-from-referencegit 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/remix-graphic-ad-from-reference)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/remix-graphic-ad-from-reference"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/remix-graphic-ad-from-reference/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/remix-graphic-ad-from-reference"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/remix-graphic-ad-from-reference.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 | $0.00136 | $0.04818 |
| Opus 5 | $0.00068 | $0.02409 |
| Sonnet 5 | $0.00027 | $0.00964 |
| Haiku 4.5 | $0.00014 | $0.00482 |
Grade A, and why
remix-graphic-ad-from-reference 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 9d 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 — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
remix-graphic-ad-from-reference
Purpose
Given one reference ad image + a target product + new copy, produce a finished static ad that keeps the reference's layout and composition but swaps the product and words for the new brand. This powers the app's "pick a Pinterest ad you like → get the same ad for your product" flow.
It does not invent layouts and it does not regenerate the whole scene from scratch. It reads the reference, then recreates it with GPT Image 2:
- GPT Image 2 (edit the reference) — ALWAYS use this as the generator. Run it in image-edit
mode on the reference itself to preserve the layout/composition and swap in the new product +
copy. This is the engine for EVERY remix (premium look). FAL slug
fal-ai/gpt-image-1/edit-image. - HTML overlay (goose-graphics) — NOT a generation engine. It is only an optional FINISHING step: if GPT bakes garbled/misspelled copy, overlay crisp text on top of the GPT output. Never use it as the primary generator — a remix must always be generated by GPT Image 2.
Inputs
| Input | Required | Notes |
|---|---|---|
reference_image |
yes | The ad to recreate (local path or URL). One image. |
product |
yes | Target product: a clean product render/photo (PNG/webp). Pull the real brand asset; grounding/swapping on it is what keeps the label correct. If the brand asset is a multi-product lineup, crop to the ONE relevant product first — the remix grounds on a single clean product per product_slot (use product_images_needed from the slot map for how many distinct products the layout needs). |
copy_changes |
optional | If omitted, the agent auto-writes it from the brand pack mapped to the template's slot_map (see Phase 0.5). New headline, benefit callouts, social-proof line, discount/badge text. Keep the reference's structure (same zones), swap the words. |
brand |
recommended | Palette (hex), font, logo/wordmark, voice — from get_brand_kit / a brand-research pack. |
style_source |
optional | template (DEFAULT) keeps the reference ad's palette/theme; brand recolours to the brand kit's documented palette. See "Brand grounding" below. The caller sets it (e.g. the user asks to "match my brand colours" → brand); absent → template. |
route_hint |
optional | Engine override. Default is always gpt_image_2; html is only a text-overlay finishing step, never the generator. |
aspect |
optional | Inherit from the reference; map to the renderer canvas. Default 4:5 / 1080×1350. |
remix_spec |
optional | The precomputed spec from the template library (slot_map + gen_prompt + remix_engine). If present, SKIP Phase 0 re-analysis — the slots and prompt are already authored. This is the normal path when remixing a library template. |
remix_mode |
from template | product (swap a physical product) or ui (SaaS/app ad — swap the app screenshot/UI, NEVER insert a product). Tagged on the template. |
app_screenshot |
for ui mode |
The brand's app/UI screenshot to drop into the device frame (used instead of product when remix_mode:ui). |
What ships with it
9 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.
- 9d ago First seen · 233 lines · 136 tokens per session scan A 522391ed2cd2
remix-graphic-ad-from-reference is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 136 tokens to every session and 4,818 once invoked, about $0.0007 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 2026-09-03.
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