ad-creative-generation — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited ad-creative-generation (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Generate ad creatives — both visuals and copy — that match a brand's identity. This skill orchestrates brand extraction, copywriting, and image generation into a single workflow.
This skill assumes the Hyper MCP is connected to your agent so the tools below are available. Brand extraction also requires Firecrawl to be configured under your Hyper integrations.
Every tool in this skill is named by its canonical tool name. Run it with the call your surface gives you:
| Surface | Find a tool | Run it |
|---|---|---|
| MCP client (Claude, Cursor, Codex, ChatGPT) | search("<what you want to do>"), then describe("<name>") | call("<name>", {...}) |
| Hyper CLI | hyperai search "<what you want to do>", then hyperai describe <name> | hyperai call <name> --json '{...}' |
If a tool is not found, its integration is not connected or not enabled for the workspace: stop and tell the user which integration to connect.
| Group | Tools |
|---|---|
| Brand extraction | firecrawl_branding_extract |
| Competitor ads | marketing_queries_start, marketing_queries_continue (stream ads.meta_library) |
| Image generation (default) | images_generate (model="gpt-image-2") |
| Image generation (text-heavy) | images_generate (model="nano-banana-pro") |
| Image generation (photoreal product shots) | images_generate (model="seedream-4.5") |
For deeper image-tool selection guidance see the image-generation skill. To turn finished creatives into running campaigns see google-ads and meta-ads.
image-generation.google-ads, meta-ads, tiktok-ads, pinterest-ads, or amazon-ads.meta-ads-library. To read the Meta ads of a known competitor by its domain or Meta page in one query, use marketing_queries_start with the ads.meta_library stream; a repeated query within a day reads the stored run at no cost.1:1 (feed), 9:16 (story), 16:9 (banner) — and quality ("draft" | "standard" | "high"); images_generate takes those, not raw pixel sizes.1024x1536), banner is 16:9 (use 1536x1024).Based on what the user needs, read the appropriate reference file:
| User Need | Reference |
|---|---|
| "Extract branding from this site" / brand colors, logo | references/brand-extraction.md |
| "Write ad copy" / headlines / variants / hooks | references/ad-copy-frameworks.md |
| Google RSAs / display ads / Performance Max assets | references/google-ads-creatives.md |
| Meta / Facebook / Instagram ads / carousel / stories | references/meta-ads-creatives.md |
When the task spans multiple areas (e.g., "create ad creatives for this website"), follow the full workflow below.
Call firecrawl_branding_extract with the website URL. This single call returns branding data, a saved logo, and a website screenshot:
brand = firecrawl_branding_extract(url="https://example.com")The result contains:
brand.logo.file_id — logo image to use as referencebrand.screenshot.file_id — website screenshot to use as referencebrand.branding — colors, typography, spacing, personalityBoth logo and screenshot are saved images ready to pass as reference_images to image generation tools. SVG logos are automatically converted to PNG, so always include the logo — no need to filter by format.
For deeper guidance on brand extraction, read `references/brand-extraction.md`.
Using the brand personality, tone, and value proposition from the extraction, write ad copy variants. Structure copy by what's being tested:
Change only one element per variant so results can be attributed to specific changes.
For copy frameworks, hook patterns, and variant strategy, read `references/ad-copy-frameworks.md`.
Generate ad images using brand assets as references. Always pass both logo and screenshot as reference images — SVG logos are automatically converted to PNG by the branding tool.
Read `brand.screenshot.description` to understand what the product actually does and what the UI looks like. Do not guess from the company name.
Preferred first pass: `images_generate` with `model="gpt-image-2"`
#### Default approach (best practice for SaaS / product ads)
By default, a strong ad creative has three layers: brand (logo), copy (headline), and product (realistic screenshot showing the core value prop). This is the recommended starting point when the user hasn't specified a creative direction. Use model="gpt-image-2" for this initial composition unless the user explicitly asks for another model or the image is primarily a text-rendering task.
images_generate(
requests=[{
"prompt": (
"Social media ad creative for [company name]. "
"Top: the [company] logo. "
"Headline: '[headline from ad copy phase or site hero text]'. "
"Below the headline: a clean, realistic product screenshot of [describe the actual UI "
"based on brand.screenshot.description]. "
"Match the brand style from the references."
),
"reference_images": [brand.logo.file_id, brand.screenshot.file_id]
}],
model="gpt-image-2",
aspect_ratio="1:1",
quality="high"
)#### Following user direction
If the user asks for a specific creative style (lifestyle imagery, abstract, illustration, people using the product, etc.), follow their direction. The defaults above are a starting point, not a constraint. The reference images still supply brand consistency regardless of creative direction.
#### Things to avoid (unless the user specifically asks)
| Scenario | Tool | Why |
|---|---|---|
| On-brand creative (default) | images_generate (model="gpt-image-2") with logo + screenshot refs | Best default for the first branded concept |
| Text-heavy creative (headlines in image) | images_generate (model="nano-banana-pro") | Use only when text rendering inside the image is the main requirement |
| Quick ideation / concept exploration | images_generate (model="gpt-image-2") | Fast first-pass concepting with no references needed |
| Iterative refinement of existing image | images_generate (model="nano-banana") with the image as a reference | Edit a specific generated image |
| Photoreal product shots / material detail | images_generate (model="seedream-4.5") | Strong fabric/texture/spatial depth |
| Platform | Format | Image Size | Key Limits |
|---|---|---|---|
| Meta Feed | 1:1 | 1080x1080 | Primary text: 125 chars visible |
| Meta Story | 9:16 | 1080x1920 | Full screen, 15s max |
| Meta Carousel | 1:1 | 1080x1080 | Up to 10 cards |
| Google RSA | N/A (text only) | N/A | 15 headlines (30 chars), 4 descriptions (90 chars) |
| Google Display | Various | 1200x628 | Responsive display ads |
For full platform specs, read `references/google-ads-creatives.md` or `references/meta-ads-creatives.md`.
When generating variants from existing top performers:
For detailed frameworks, read `references/ad-copy-frameworks.md`.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.