AgentSkillsCN

ecom-ai-image-ads

基于基础文档与竞品广告案例,生成每日电商图像广告计划与提示词组合;其中包含“优胜者→变体”循环机制,以及创意库标签管理功能。

SKILL.md
--- frontmatter
name: ecom-ai-image-ads
description: "Generate a daily ecom image-ad plan + prompt packs from foundation docs and competitor ad examples; includes a winner→variants loop and creative registry tagging."

Ecom AI Image Ads (Plan → Prompts → Variants)

This skill produces a daily creative plan and prompt packs you can run in your image tool of choice (Gemini/MJ/SDXL), built from your angle matrix.

Required inputs

  • Workspace with foundation docs + ads/ads.csv (from ecom-foundation-docs)
  • Competitor ad examples (URLs, screenshots, or notes on what’s working)

Required outputs (create these files)

In outputs/ecom/<brand_slug>/<run_id>/creative/:

  • plan.yaml (what to make; format/aspect/angle mapping)
  • prompts.md (copy/paste prompt pack with variants)
  • winner_variations.md (prompt pack for “20 variants of winner”)

Daily creative plan rules (DTC)

For each angle, generate a balanced set:

  • UGC look (authentic, imperfect, believable)
  • Product hero (clean, DTC aesthetic, benefits visible)
  • Proof-first (reviews, demo frames, ingredient/mechanism visual)
  • Comparison/how-to (simple “why it works” visuals; avoid policy landmines)

Aspect ratios to cover:

  • 1:1, 4:5, 9:16

Prompt structure (recommended)

Each prompt should include:

  • subject + setting (UGC/home, bathroom, gym, kitchen, etc.)
  • mechanism/proof (what’s visually different)
  • shot type (selfie, handheld, product close-up, before/after only if true/allowed)
  • lighting + lens (phone look vs studio)
  • negative constraints (no text overlay, no logos, no medical claims)

Winner → variants loop

When you identify a winner, generate 10–30 variants that preserve the “why it worked”:

  • change background, wardrobe, framing, angle, props
  • keep mechanism + core visual cue consistent
  • keep “UGC authenticity” (avoid over-polish)

Output these as winner_variations.md with explicit instructions for subtle vs moderate changes.

Registry tagging (for learning loop)

Tag each creative with:

  • brand:<slug>
  • product:<slug>
  • angle:<angle_id>
  • format:<ugclook|product|proof|comparison|howto>
  • aspect:<1:1|4:5|9:16>

Use ecom-learning-loop to store prompt → performance so you can generate variants from data.