kdp-keyword-optimizer_skill

Overview

This skill optimizes the seven backend keyword slots for Amazon KDP books to improve discoverability under Amazon's A10 algorithm and Rufus AI. It recommends seven semantically relevant long-tail phrases (≤50 characters each) and a slot-by-slot strategy so your metadata matches reader intent, not just exact matches. Use it when filling or refreshing KDP backend keywords to increase relevant search impressions.

How this skill works

I extract your book’s core themes (topic, audience, outcome, emotional appeal, comparable works) and convert them into 3–5 word long-tail semantic phrases. I enforce Amazon rules and the 50-character limit, prioritize high-volume phrases for slots 1–2, and allocate remaining slots to secondary themes, comparables, and category-cementing phrases. Optionally I validate keywords against search volume data to prioritize choices.

When to use it

• Filling the 7 KDP backend keyword boxes before publishing
• Refreshing keywords for underperforming titles
• Optimizing discoverability for a new marketing push
• Aligning metadata with semantic search and Rufus AI intent
• Prioritizing high-volume, relevant phrases for key slots

Best practices

• Extract core themes: primary topic, target reader, outcome, emotional hook, comparable books
• Build 3–5 word long-tail phrases combining audience + topic + outcome
• Avoid title/subtitle duplicates, competitor names, subjective claims, and misspellings
• Keep each slot ≤50 characters and use phrases (not single words)
• Place highest-volume, most relevant phrases in slots 1–2; reserve slot 7 for category-cementing terms
• Refresh keywords every 3–6 months and test changes incrementally

Example use cases

• Catholic Lenten devotional: create audience+season+format phrases and a category-cementing slot
• Health crossover memoir: blend medical terms with emotional outcomes for broad discovery
• Niche nonfiction: prioritize specific long-tail queries in slots 1–4 and comparables in 5–6
• Underperforming title: audit slots for duplicates, replace single words with semantic phrases, and validate volumes
• Series launch: avoid title repetition across slots and use comparables to capture reader overlap