Kunze Ad Setup

SkillDev tools

Codex-native Amazon PPC setup workflow using Kunze's broader ecosystem-driven strategy. Use when the user wants LaunchFast-driven bulk-sheet generation with broad and phrase coverage, gap analysis, and a campaign package written to disk.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Kunze Ad Setup skill

What this skill tells your AI

The instructions your AI receives, as published by hashgraph-online/awesome-codex-plugins in plugins/BlockchainHB/launchfast_codex_plugin/skills/kunze-ad-setup/SKILL.md and read by ahel’s review.

Inputs

Ask once for:

  • main keyword
  • product SKU
  • optional product name
  • optional budget level: conservative or aggressive
  • optional output path

Defaults:

  • budget level: conservative
  • output directory: ./artifacts/launchfast/campaigns/

Strategy

Kunze’s model favors:

  • broad and phrase coverage
  • one ad group per campaign
  • small keyword sets
  • gap-opportunity terms where competitors rank poorly

Workflow

1. Market research

Run:

research_products(keyword="<main_keyword>", focus="balanced", product_limit=20)

Collect top 10-15 competitor ASINs plus market context.

2. Keyword research

  • Research competitor ASINs in manageable batches of 3-4.
  • Prefer parallel tool calls where possible.
  • Do not require delegation.

Use:

amazon_keyword_research(asins=[...], limit=50, min_search_volume=300)

3. Build the keyword master list

For each keyword compute:

  • overlap across ASIN batches
  • search volume
  • CPC
  • purchase rate
  • relevance
  • competitor coverage
  • gap-opportunity signal

Then select:

  • Broad campaign keywords
  • Phrase campaign keywords
  • ASIN targets
  • Category target placeholder if category ID is unknown

4. Generate bulksheet

Create:

  • Auto campaign
  • Broad campaign
  • Phrase campaign
  • Category targeting campaign
  • ASIN targeting campaign

Use deterministic CSV generation with Python csv.writer.

Use this exact Amazon Bulksheets 2.0 header and column order:

Product,Entity,Operation,Campaign Id,Ad Group Id,Portfolio Id,Ad Id,Keyword Id,Product Targeting Id,Campaign Name,Ad Group Name,Start Date,End Date,Targeting Type,State,Daily Budget,sku,asin,Ad Group Default Bid,Bid,Keyword Text,Match Type,Bidding Strategy,Placement,Percentage,Product Targeting Expression,Audience ID,Shopper Cohort Percentage,Shopper Cohort Type

Deterministic campaign layout:

  • Auto: 1 campaign, 1 ad group, 1 product ad, 4 auto targeting rows
  • Broad: 1 campaign, 1 ad group, 1 product ad, up to 5 broad-match keywords
  • Phrase: 1 campaign, 1 ad group, 1 product ad, up to 5 phrase-match keywords
  • Category: 1 campaign, 1 ad group, 1 product ad, 1 category targeting row
  • ASIN: 1 campaign, 1 ad group, 1 product ad, up to 15 ASIN target rows

Required defaults:

  • start date: current date in YYYYMMDD
  • bidding strategy: Dynamic bids - down only
  • one ad group per campaign
  • if category ID is unknown, emit a literal placeholder such as [CATEGORY_ID]

Write to:

./artifacts/launchfast/campaigns/[product-name]-kunze-[YYYY-MM-DD].csv

5. Provide an operator summary

Return:

  • campaign list
  • selected keywords
  • budget assumptions
  • output file path

If a category ID is missing, leave a clear placeholder and call it out explicitly.

Signals

GitHub stars
985
Forks
276
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
kunze-ad-setup
Source
github.com/hashgraph-online/awesome-codex-plugins