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Search Listing Optimizer

面向 Amazon、淘宝、京东、TikTok Shop、小红书、Shopify 卖家的商品 listing 搜索优化技能:依据内置关键词密度、搜索意图与属性完整性框架,审计标题、卖点、描述、图片与评价,检测转化陷阱,输出含关键词机会图、属性评分卡与优先行动清单的 Markdown 优化简报;不接入实时搜索分析或平台接口。

harrylabsj
harrylabsj
热度 34.92
最近更新 2026-06-06 05:10:48
分类:营销依赖:纯提示词应用场景:市场分析 / 文案创作 / 社交媒体 / 模板

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add search-listing-optimizer
Metadata
name
search-listing-optimizer
description
Optimize ecommerce product listings for Amazon A9, Taobao/1688 search, JD search, TikTok Shop discovery, Xiaohongshu SEO, and Shopify storefront search using keyword density frameworks, attribute-completeness checklists, and conversion-trap detection. Use when sellers need a listing audit, keyword refresh, or conversion improvement brief without live search analytics or platform API access.

Search Listing Optimizer

Overview

Use this skill to audit a product listing and generate an optimization brief covering keyword targeting, attribute completeness, image metadata, and conversion-trap detection. It applies built-in search-ranking heuristics and best-practice libraries to surface actionable improvements.

This MVP is heuristic. It does not connect to live search analytics, A9 algorithms, or platform seller portals. It relies on the user's provided listing notes and product context.

Trigger

Use this skill when the user wants to:

  • audit an Amazon, Taobao, JD, TikTok Shop, Xiaohongshu, or Shopify listing for search visibility
  • identify missing keywords, weak attributes, or conversion traps in existing copy
  • rebuild a listing keyword strategy for a new product or category entry
  • compare listing quality across multiple marketplaces
  • generate a before-and-after optimization brief for a product team

Example prompts

  • "Audit our Amazon skincare listing for A9 visibility"
  • "Help me optimize our Taobao product listing for crowd-collapse ranking"
  • "What's wrong with our JD listing that gets traffic but no conversions?"
  • "Create an optimization brief for our new TikTok Shop product"

Workflow

  1. Capture the platform, product context, and optimization goal.
  2. Apply keyword-density and search-intent frameworks for the target platform.
  3. Assess attribute completeness across key fields.
  4. Detect common conversion traps (pricing, images, reviews, description).
  5. Return a markdown optimization brief with prioritized action items.

Inputs

The user can provide any mix of:

  • platform: Amazon, Taobao, 1688, JD, TikTok Shop, Xiaohongshu, Shopify, general
  • product category: category name, subcategory, price range
  • current listing notes: title, bullet points, description, keywords, images, reviews
  • optimization goal: visibility boost, conversion improvement, new listing, relaunch
  • competitor context: competitor ASINs, titles, or keyword strategies (optional)

Outputs

Return a markdown brief with:

  • platform search algorithm summary (how ranking works on that platform)
  • keyword opportunity map (search volume intent × competition)
  • listing attribute scorecard (title, bullets, description, backend keywords, images)
  • conversion-trap detection (pricing, trust signals, review depth, description clarity)
  • prioritized action list with expected impact
  • template for revised title, bullets, or description

Safety

  • No live search analytics, ad console, or seller portal access.
  • Optimization recommendations are directional; actual ranking depends on platform algorithms.
  • Do not claim guaranteed ranking improvements or sales lift.
  • Pricing and promotional decisions remain with the operator.

Best-fit Scenarios

  • sellers preparing new listings or refreshing existing ones for better visibility
  • teams managing multiple marketplace accounts needing a consistent audit framework
  • brands expanding to new platforms and needing a listing best-practice brief

Not Ideal For

  • real-time rank tracking, automated listing updates, or live ad campaign management
  • products in highly regulated categories with strict claim restrictions
  • very early-stage products with no sales history or review data

Acceptance Criteria

  • Return markdown text.
  • Include attribute scorecard, keyword opportunity map, and prioritized action list.
  • Make ranking assumptions explicit.
  • Keep the brief practical for marketplace sellers and listing specialists.