/community/ad creative
innernet
docsskillscommunitycompanydeveloperssecurityprivacytermscontact

a skill by indranilbanerjee, brought here by kt

ad creative

paste this link into your ai. it will know what to do.

/skills/indranilbanerjee-ad-creative

Generate 3-5 ad copy variations per platform — headlines, descriptions, and CTAs formatted to Google, Meta, LinkedIn, TikTok, X, and Pinterest specs — each scored 1-10 with policy-compliance flags, A/B testing groupings, and a message-match check against the landing page. Triggers on \"/digital-marketing-pro:ad-creative\", \"write ad copy for Meta\", \"give me RSA headline variations\", \"we need LinkedIn ad copy\", \"draft TikTok ad creative\". Reads the brand profile, guidelines, and compliance rules; routes video ad scripts to /digital-marketing-pro:video-script and gates AI-generated visua

kindskill
last tended2026-11-01
written byindranilbanerjee
sourcegithub.com/indranilbanerjee/digital-marketing-pro
kept currentwith its source · last read 2026-11-03
savedonce, into someone's innernet
brought here bykt
reuseMIT
yours?it stays under your name. to change it or take it down, write to connect@innernet.live
reading4 min

/digital-marketing-pro:ad-creative

Purpose

Generate high-performing ad copy variations tailored to specific platforms and formats. Each variation is scored for quality and compliance, with recommendations for testing strategy.

Input Required

The user must provide (or will be prompted for):

  • Product/service: What is being advertised
  • Platform(s): Google Ads, Meta (Facebook/Instagram), LinkedIn, TikTok, X, Pinterest
  • Ad format: RSA, single image, carousel, video script, story, etc. For video ad scripts (6s bumper, 15s skippable, 30s spot, UGC-style), route to /digital-marketing-pro:video-script — its step 2.4 carries the per-format structural rules (the 5-second skip deadline, one-message bumpers, native-style disclosure) and its output passes the /check gate. This skill owns the copy layer around the video: headlines, descriptions, and CTAs.
  • Campaign objective: Awareness, traffic, leads, conversions, app installs
  • Target audience: Who the ads are for
  • Key offer/CTA: Promotion, value prop, or desired action
  • Landing page URL: Where the ad will drive traffic (optional)

Process

  1. 1Load brand context: Read ~/.claude-marketing/brands/_active-brand.json for the active slug, then load ~/.claude-marketing/brands/{slug}/profile.json. Apply brand voice, compliance rules for target markets (skills/context-engine/compliance-rules.md), and industry context. Also check for guidelines at ~/.claude-marketing/brands/{slug}/guidelines/_manifest.json — if present, load restrictions and relevant category files. Check for custom templates at ~/.claude-marketing/brands/{slug}/templates/. Check for agency SOPs at ~/.claude-marketing/sops/. If no brand exists, ask: "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults.
  2. 2Identify platform-specific constraints: character limits, format requirements, policy restrictions. For X, read the ad-text rows in scripts/paid_products.json (reported: no hashtag in the ad text, at most one emoji, the URL in the card, not the text)
  3. 3Generate 3-5 ad copy variations per platform, each with a distinct angle (benefit, urgency, social proof, curiosity, direct)
  4. 4Score each variation on: brand alignment, clarity, emotional impact, CTA strength, policy compliance
  5. 5Flag any potential policy violations (restricted claims, prohibited language)
  6. 6Recommend A/B testing groupings and priority order
  7. 7If landing page URL is provided, check message match between ad and page

Output

Per platform, a set of ad copy variations including:

  • Headlines, descriptions, and CTAs formatted to platform specifications
  • Quality score (1-10) with reasoning per variation
  • Policy compliance check with flagged issues
  • A/B testing recommendation with hypothesis for each test
  • Message match assessment (if landing page provided)
  • Creative direction notes for visual/video assets (see AI image/video generation guidance below)

AI image & video generation guidance (May 2026)

When the brief includes static visuals or short-form video, recommend the model that fits the use case and call out the compliance overhead:

Asset typeRecommended model (May 2026)When to useCompliance note
Product hero stills, lifestyle photography, e-commerce tilesGoogle Nano Banana Pro (Gemini 3 Pro Image, multi-image composition, character/object consistency)Strong text rendering inside images (logos, on-pack copy), brand-character consistency across a campaign, high-fidelity product realism.Outputs ship with SynthID watermarking by default; ALSO sign with C2PA via /digital-marketing-pro:c2pa-metadata before any EU distribution.
Short-form social video (≤8s reels, organic vertical)A video model with synchronized native audio. The model depends on the backend: resolve latest-video-google (Vertex AI) or latest-video-gemini-api (Gemini API) with resolve_model.py; a Gemini API key alone can't call the Vertex modelReels, TikTok, Shorts cut-downs, ad-creative experimentation.Synthetic-voice / synthetic-human content must carry a visible deepfake disclosure under EU Article 50 — see skills/context-engine/compliance-rules.md §1.1b.
Long-form video with native audio / multi-modal storytellingGemini Omni (multimodal generation, May 2026 I/O launch — text + image + audio + video unified)Connected-content campaigns where a single brief produces a hero film, social cut-downs, audio version, and stills consistently. Best for brands with disciplined creative governance — Omni's range outpaces most brand-safety review processes.Default Omni outputs carry SynthID + Gemini provenance markers. Add C2PA before EU publish. Run synthetic-person outputs past Legal — Omni's photoreal humans frequently hit "substantial AI manipulation" thresholds under Article 50.
Static image — fast iteration / mood-boardingOpenAI gpt-image-2, Midjourney v7, Adobe FireflyInternal mood boards, concept exploration. Not for shipped EU creative without C2PA.Adobe Firefly applies Content Credentials to images it fully generates ("where 100% of the pixels are generated using Adobe Firefly", helpx.adobe.com); for the others, check the file with embed-c2pa.py --verify instead of assuming. Before EU publish, sign with /digital-marketing-pro:c2pa-metadata to add the c2pa.ai-disclosure assertion.

Workflow recommendation:

  1. 1Brief the visual concept in this skill's output (subject, composition, brand-character constraints, on-pack text if any).
  2. 2Hand the visual spec to whichever production track owns image/video — your design team, any AI image/video tool (the model table above maps use-case → generator), or a connected design platform (e.g. the Canva / Figma MCP connectors listed in /digital-marketing-pro:integrations). The spec is deliberately tool-agnostic: any production track can consume it unchanged.
  3. 3Treat all AI-generated visuals as Article 50 in-scope until proven otherwise. The pre-publish gate (/digital-marketing-pro:check) blocks unsigned AI assets for EU-targeted campaigns.

Agents Used

  • content-creator — Ad copy generation, angle development, CTA crafting
  • media-buyer — Platform specs, policy compliance, testing strategy
  • brand-guardian — Voice alignment, compliance review, claim verification

keep it where your ai can reach it.

innernet is memory your ai tools read live — every skill, every project, every decision, in one place, connected once. save this skill to yours, or publish one of your own as a link like this.

save it to your innernetsee every skill