ads-next

Analyze ad audit JSON files to generate prioritized improvement plans for Meta, Google, and TikTok campaigns.

58|12|Updated Apr 29, 2026
One-click install
npx skills add https://github.com/Hainrixz/claude-ads --skill ads-next
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ads-next
Source: https://github.com/Hainrixz/claude-ads/tree/main/skills/ads-next
Command: npx skills add https://github.com/Hainrixz/claude-ads --skill ads-next

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python3, and includes scripts (resource) components.

What problem does it solve?

This skill solves the problem of audit fatigue and lack of actionable direction by turning static ad audit results into a prioritized, step-by-step coaching plan.

Core Features & Use Cases

  • Continuous Coaching: Automatically ranks Quick Wins and Critical Issues across Meta, Google, and TikTok ads based on impact and effort.
  • Regression Detection: Monitors health score changes between audits to flag performance drops as Priority 0 alerts.
  • Guided Remediation: Provides an interactive, step-by-step walk-through to fix identified issues, ensuring you always know exactly what to improve next.

Quick Start

Ask the assistant to recommend the next steps for your ad campaigns to receive a ranked list of high-impact fixes.

Frequently Asked Questions about ads-next

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I get actionable steps from ad audit results for Meta, Google, and TikTok?

Ad audit results are transformed into actionable steps by analyzing multi-platform performance data to generate prioritized improvement plans. The system ranks fixes based on calculated impact-versus-effort scores to guide your technical remediation.

How does regression detection work for advertising campaign health scores?

Regression detection for advertising campaigns works by monitoring health score changes between sequential audit JSON files. When performance drops are flagged, the system automatically categorizes them as Priority 0 alerts to ensure critical issues are addressed immediately.

Do I need Python 3 to run local advertising audit scripts?

You need Python 3 installed locally to execute the required profile management scripts. These scripts maintain the state and history necessary for continuous AI coaching and iterative ad campaign remediation.

What is the best way to prioritize Quick Wins and Critical Issues across ad platforms?

The best way to prioritize Quick Wins and Critical Issues across ad platforms is to evaluate their impact-versus-effort scores. This automated ranking system identifies high-impact fixes across Meta, Google, and TikTok campaigns to eliminate audit fatigue.

Can I use this ad coaching system without local audit JSON files?

You cannot use this ad coaching system without local audit JSON files. Access to these files is strictly required to analyze performance regressions, calculate impact scores, and maintain your remediation history state.

Why does guided remediation provide a step-by-step walk-through for ad campaigns?

Guided remediation provides a step-by-step walk-through to ensure you always know exactly what to improve next. It interactively directs you through iterative technical fixes for your Meta, Google, and TikTok campaigns based on prioritized audit data.