amazon-listing-builder

Build a layered keyword library, a user question library, and an evidence library first, then generate titles, bullets, A+ modules, Search Terms, and QA from that data. Finish with compliance, keyword coverage, semantic coverage, and conversion-logic checks before publishing.

Structure five bullets as a decision chain: core value, pain-point resolution, usage scenarios, specifications, and trust. Each bullet pairs one claim with concrete evidence such as materials, test data, or certifications, and avoids empty words like premium or perfect.

SellerSprite MCP is strongly recommended for keyword volume, competitor ASIN details, and review data, and the skill forbids scraping Amazon pages as a substitute. It can still work from user-supplied product information and keyword lists, with missing fields marked DATA_MISSING.

No. AI output must be human-reviewed for compliance risks like absolute claims, medical or eco promises, evidence authenticity, keyword relevance, and field length limits such as the 200-character US title and 250-byte Search Terms caps.

Red-line terms include 100%, never, lifetime, best, cures, FDA approved without certification, and 100% eco-friendly. The skill replaces them with safer phrasing such as help reduce, designed for long-term use, and made with recyclable materials.

Monitor CTR daily in week one, run keyword performance analysis weekly during weeks two to four, optimize monthly for the first quarter, and do quarterly refinements afterward using ad reports, QA additions, and review themes.