菜单
Multi-platform paid advertising audit and optimization skill. Analyzes Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, and Apple Search Ads. 225+ checks with scoring, parallel agents, industry templates, and AI creative generation.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | ads |
| description | Multi-platform paid advertising audit and optimization skill. Analyzes Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, and Apple Search Ads. 225+ checks with scoring, parallel agents, industry templates, and AI creative generation. |
| argument-hint | audit | google | meta | youtube | linkedin | tiktok | microsoft | apple | creative | landing | budget | plan <type> | competitor | dna <url> | create | generate | photoshoot |
| license | MIT |
Comprehensive ad account analysis across all major platforms (Google, Meta, LinkedIn, TikTok, Microsoft). Orchestrates 17 specialized sub-skills and 10 agents (6 audit + 4 creative).
| Command | What it does |
|---|---|
/ads audit | Full multi-platform audit with parallel subagent delegation |
/ads google | Google Ads deep analysis (Search, PMax, YouTube) |
/ads meta | Meta Ads deep analysis (FB, IG, Advantage+) |
/ads youtube | YouTube Ads specific analysis |
/ads linkedin | LinkedIn Ads deep analysis (B2B, Lead Gen) |
/ads tiktok | TikTok Ads deep analysis (Creative, Shop, Smart+) |
/ads microsoft | Microsoft/Bing Ads deep analysis (Copilot, Import) |
/ads creative | Cross-platform creative quality audit |
/ads landing | Landing page quality assessment for ad campaigns |
/ads budget | Budget allocation and bidding strategy review |
/ads plan <business-type> | Strategic ad plan with industry templates |
/ads apple | Apple Search Ads (ASA) deep analysis |
/ads competitor | Competitor ad intelligence analysis |
/ads dna <url> | Extract brand DNA from website, outputs brand-profile.json |
/ads create | Generate campaign concepts + copy briefs, outputs campaign-brief.md |
/ads generate | Generate AI ad images from brief, outputs to ad-assets/ |
/ads photoshoot | Product photography in 5 styles (Studio, Floating, Ingredient, In Use, Lifestyle) |
Before any audit or analysis, collect this context. Without it, benchmarks will be generic and recommendations may be wrong for the user's situation.
Ask these questions upfront (combine into one message):
If the user provides data upfront (e.g. "audit my Google Ads, I spend $5k/mo on SaaS"), extract context from that and proceed without re-asking.
Use the provided context to:
references/benchmarks.mdWhen the user invokes /ads audit, delegate to subagents in parallel:
context: fork: audit-google, audit-meta, audit-creative, audit-tracking, audit-budget, audit-complianceFor individual commands (/ads google, /ads meta, etc.), load the relevant
sub-skill directly. Still collect context first if not already provided.
Sequential pipeline (each step is independently runnable):
/ads dna <url> → brand-profile.json in current directory/ads create → reads profile + optional audit results → campaign-brief.md/ads generate → reads brief + profile → ad-assets/ directory/ads photoshoot → standalone or reads profile for style injectionRequires GOOGLE_API_KEY (Gemini default) or ADS_IMAGE_PROVIDER + matching key.
If API key is missing, /ads generate and /ads photoshoot display setup
instructions and exit; they never fail silently.
Detect business type from ad account signals:
Hard rules (never violate these):
Load these on-demand as needed; do NOT load all at startup.
Path resolution: All references are installed at ~/.claude/skills/ads/references/.
When sub-skills or agents reference ads/references/*.md, resolve to
~/.claude/skills/ads/references/*.md.
references/scoring-system.md: Weighted scoring algorithm and grading thresholdsreferences/benchmarks.md: Industry benchmarks by platform (CPC, CTR, CVR, ROAS)references/bidding-strategies.md: Bidding decision trees per platformreferences/budget-allocation.md: Platform selection matrix, scaling rules, MERreferences/platform-specs.md: Creative specifications across all platformsreferences/conversion-tracking.md: Pixel, CAPI, EMQ, ttclid implementationreferences/compliance.md: Regulatory requirements, ad policies, privacyreferences/google-audit.md: 74-check Google Ads audit checklistreferences/meta-audit.md: 46-check Meta Ads audit checklistreferences/linkedin-audit.md: 25-check LinkedIn Ads audit checklistreferences/tiktok-audit.md: 25-check TikTok Ads audit checklistreferences/microsoft-audit.md: 20-check Microsoft Ads audit checklistreferences/brand-dna-template.md: Brand DNA schema and extraction guidereferences/image-providers.md: Provider config (Gemini/OpenAI/Stability/Replicate)references/google-creative-specs.md: PMax/RSA/YouTube generation-ready specsreferences/meta-creative-specs.md: Feed/Reels/Stories specs + safe zonesreferences/linkedin-creative-specs.md: Single image/video B2B constraintsreferences/tiktok-creative-specs.md: 9:16 only + safe zone overlayreferences/youtube-creative-specs.md: Skippable/Bumper/Shorts/Thumbnailreferences/microsoft-creative-specs.md: Multimedia Ads + RSA subsetreferences/gaql-notes.md: GAQL field compatibility, deduplication patterns, filter scope best practicesreferences/voice-to-style.md: Brand voice axis to visual attribute mapping for image generationreferences/copy-frameworks.md: 6 ad copy frameworks (AIDA, PAS, BAB, 4P, FAB, Star-Story-Solution)Per-platform score using weighted algorithm from references/scoring-system.md.
Cross-platform aggregate weighted by budget share:
Aggregate = Sum(Platform_Score x Platform_Budget_Share)
| Grade | Score | Action Required |
|---|---|---|
| A | 90-100 | Minor optimizations only |
| B | 75-89 | Some improvement opportunities |
| C | 60-74 | Notable issues need attention |
| D | 40-59 | Significant problems present |
| F | <40 | Urgent intervention required |
This skill orchestrates 17 specialized sub-skills:
For parallel analysis during full audits:
audit-google: Google Ads checks (G01-G74)audit-meta: Meta Ads checks (M01-M46)audit-creative: Creative quality for LinkedIn, TikTok, Microsoftaudit-tracking: Conversion tracking health across all platformsaudit-budget: Budget, bidding, structure for LinkedIn, TikTok, Microsoftaudit-compliance: Compliance, settings, performance across all platformscreative-strategist: Campaign concepts from brand profile + audit results (Opus, maxTurns: 25)visual-designer: Image generation with brand injection via generate_image.py (Sonnet, maxTurns: 30)copy-writer: Headlines, CTAs, primary text within platform limits (Sonnet, maxTurns: 20)format-adapter: Asset dimension validation and spec compliance reporting (Haiku, maxTurns: 15)Apple Search Ads (ASA) deep analysis for mobile app advertisers. Evaluates campaign structure, bid health, Creative Sets, MMP attribution, budget pacing, TAP coverage (Today/Search/Product Pages), and goal CPA benchmarks by country. Use when user says Apple Search Ads, ASA, App Store ads, Apple ads, Search Ads, or is advertising a mobile app on iOS.
Competitor ad intelligence analysis across Google, Meta, LinkedIn, TikTok, and Microsoft. Analyzes competitor ad copy, creative strategy, keyword targeting, estimated spend, and identifies competitive gaps and opportunities. Use when user says competitor ads, ad spy, competitive analysis, competitor PPC, or ad intelligence.
Campaign concept and copy brief generator for paid advertising. Reads brand-profile.json and optional audit results to produce structured campaign concepts, messaging pillars, and copy briefs. Outputs campaign-brief.md to the current directory. Run after /ads dna and before /ads generate. Triggers on: create campaign, campaign brief, ad concepts, write ad copy, campaign strategy, ad messaging, creative brief, generate concepts.
Brand DNA extractor for paid advertising. Scans a website URL to extract visual identity, tone of voice, color palette, typography, and imagery style. Outputs brand-profile.json to the current directory. Run before /ads create or /ads generate for brand-consistent creative. Triggers on: brand DNA, brand profile, extract brand, brand identity, brand colors, what is the brand voice, analyze brand, brand style guide.
AI image generation for paid ad creatives. Reads campaign-brief.md and brand-profile.json to produce platform-sized ad images using banana-claude. Requires banana-claude (v1.4.1+) with nanobanana-mcp configured. Triggers on: generate ads, create images, make ad creatives, generate visuals, create ad images, generate campaign images, make the images, generate from brief.
Landing page quality assessment for paid advertising campaigns. Evaluates message match, page speed, mobile experience, trust signals, form optimization, and conversion rate potential. Use when user says landing page, post-click experience, landing page audit, conversion rate, or landing page optimization.