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agricidaniel/ads-google

Führt eine umfassende Google Ads-Analyse zu Search, Performance Max, AI Max, Display, YouTube und Demand Gen Kampagnen durch.

Was ist ads-google?

Dieses Skill unterstützt Entwickler und KI-Agenten dabei, Google Ads-Konten in der Tiefe zu analysieren. Es deckt 80 Prüfpunkte über verschiedene Bereiche ab, darunter Conversion-Tracking, verschwendete Ausgaben, Account-Struktur, Keywords, Anzeigen und Einstellungen. Besondere Schwerpunkte liegen auf AI Max (mit Suche-Begriff-Matching, AI Brief, Textanpassung, FUE und Markenausschlüssen) sowie Smart Bidding-Signalen. Das Skill ist ideal für Situationen, in denen ein Nutzer nach „Google Ads“, „Google PPC“, „Search Ads“, „PMax“, „Performance Max“, „AI Max“, „AI Brief“, „Broad Match Audit“, „Quality Score Check“, „Search Terms Audit“, „Smart Bidding“ oder „Google Campaign“ fragt. Es analysiert Kampagnen auf Search, Performance Max, Display, YouTube und Demand Gen und liefert detaillierte Verbesserungsvorschläge und Optimierungsmöglichkeiten.

Funktioniert mit~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/agricidaniel/claude-ads/tree/main/skills/ads-google

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Dokumentation

Was macht ads-google?

Führt eine umfassende Google Ads-Analyse durch. Abgedeckt werden Search, Performance Max, AI Max, Display, YouTube und Demand Gen Kampagnen. Bewertet 80 Prüfpunkte zu Conversion-Tracking, verschwendeten Ausgaben, Account-Struktur, Keywords, Anzeigen und Einstellungen. Beinhaltet AI Max (Suche-Begriff-Matching, AI Brief, Textanpassung, FUE, Markenausschlüsse) und Smart Bidding-Signale. Verwenden, wenn der Nutzer Begriffe wie Google Ads, Google PPC, Search Ads, PMax, Performance Max, AI Max, AI Brief, Broad Match Audit, Quality Score Check, Search Terms Audit, Smart Bidding oder Google Campaign erwähnt.

Individual skills in this repo

This repo contains 3 individual skills — each has its own dedicated page.

agricidaniel/ads

Multi-platform paid advertising audit and optimization skill. Analyzes Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, and Amazon Ads. 250+ checks with scoring, parallel agents, industry templates, AI creative generation, attribution and server-side tracking deep dives.

agricidaniel/ads-meta

Meta Ads deep analysis covering Facebook, Instagram, and Threads advertising in the Andromeda + GEM + Lattice era. Evaluates 50 checks across Pixel/CAPI health, creative diversity and Entity-ID clustering risk, account structure, ASC/AAC defaults for Sales/Leads/App, and audience targeting. Includes Advantage+ assessment and creative-as-targeting scoring. Use when user says Meta Ads, Facebook Ads, Instagram Ads, Threads ads, Advantage+, ASC, AAC, Andromeda, GEM, Lattice, Entity-ID clustering, creative diversity, Sales optimization, Leads optimization, App optimization, or Meta campaign.

agricidaniel/ads-tiktok

TikTok Ads deep analysis covering creative quality, tracking, bidding, campaign structure, and TikTok Shop under the TikTok USDS Joint Venture (post Jan 2026 divestiture). Evaluates 28 checks with emphasis on creative-first strategy, safe zone compliance, creative diversity for retrieval, and Smart+ campaigns. Use when user says TikTok Ads, TikTok marketing, TikTok Shop, Spark Ads, Smart+, USDS, creative diversity for retrieval, or TikTok campaign.

Verwandte Skills

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

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affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

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affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

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affaan-m/everything-claude-code

The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

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forrestchang/andrej-karpathy-skills

Agent skill repository discovered by 10x-chat research.

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langgenius/backend-code-review

Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.

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