針對 Facebook、Instagram 和 Threads 廣告進行深度分析，涵蓋 Andromeda + GEM + Lattice 時代的廣告策略評估。
此技能專為 Meta 廣告生態系統的深度審計而設計，特別針對 Andromeda、GEM 與 Lattice 等新興演算法時代的需求。它能執行多達 50 項檢查，範圍涵蓋 Pixel/CAPI 健康度、創意多樣性與 Entity-ID 集群風險、帳戶結構、Sales/Leads/App 等目標的 ASC/AAC 預設值，以及受眾定位策略。此外，還包含 Advantage+ 廣告活動的評估與創意即目標定位的評分。使用者只要提及 Meta Ads、Facebook Ads、Instagram Ads、Threads ads、Advantage+、ASC、AAC、Andromeda、GEM、Lattice、Entity-ID 集群、創意多樣性、Sales 最佳化、Leads 最佳化、App 最佳化或 Meta 廣告活動等關鍵詞，即可觸發此技能。它支援 Claude Code 等 AI 代理平台，協助開發者與行銷人員快速診斷廣告帳戶的潛在問題，並提供資料驅動的優化建議，以提升廣告成效。
npx skills add https://github.com/agricidaniel/claude-ads/tree/main/skills/ads-metaInstalled? Explore more 研究與資料分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
針對 Meta 廣告進行深度分析，涵蓋 Facebook、Instagram 和 Threads 在 Andromeda + GEM + Lattice 時代的廣告策略。執行 50 項檢查，範圍包括 Pixel/CAPI 健康度、創意多樣性與 Entity-ID 集群風險、帳戶結構、Sales/Leads/App 的 ASC/AAC 預設值，以及受眾定位。包含 Advantage+ 評估與創意即目標定位評分。當使用者提及 Meta Ads、Facebook Ads、Instagram Ads、Threads ads、Advantage+、ASC、AAC、Andromeda、GEM、Lattice、Entity-ID 集群、創意多樣性、Sales 最佳化、Leads 最佳化、App 最佳化或 Meta 廣告活動時，即可使用此技能。
This repo contains 3 individual skills — each has its own dedicated page.
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.
Google Ads deep analysis covering Search, Performance Max, AI Max, Display, YouTube, and Demand Gen campaigns. Evaluates 80 checks across conversion tracking, wasted spend, account structure, keywords, ads, and settings. Includes AI Max (search-term-matching, AI Brief, text customization, FUE, brand exclusions) and Smart Bidding signals. Use when user says Google Ads, Google PPC, search ads, PMax, Performance Max, AI Max, AI Brief, broad match audit, Quality Score check, search terms audit, Smart Bidding, or Google campaign.
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.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
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.