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@naveedharri · 收录于 1 周前

Comprehensive paid advertising audit and optimization for any business type. Performs full multi-platform audits (Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, Microsoft Ads), single-platform deep analysis, conversion tracking health checks, creative quality assessment, budget allocation optimization, bidding strategy evaluation, and compliance verification. Industry detection for SaaS, e-commerce, local service, B2B enterprise, info products, mobile app, real estate, healthcare, finance, and agency. Triggers on: "ads", "PPC", "paid advertising", "Google Ads", "Meta Ads", "Facebook Ads", "LinkedIn Ads", "TikTok Ads", "Microsoft Ads", "Bing Ads", "ad audit", "campaign audit", "ROAS", "conversion tracking", "creative fatigue", "bid strategy".

适合你,如果你管理多个广告账户并希望提升ROAS。

/ 下载安装
ads.skill双击,或拖进 Claude 桌面版 / Cowork,即完成安装↓ .skill↓ .zip
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
Claude Code~/.claude/skills/(项目级 .claude/skills/)
Codex CLI~/.codex/skills/
Cursor自动读取上面两处目录
其他工具见其文档的「skills」目录;两个下载是同一份文件,只是名字不同
/ 通过 npx 安装 校验哈希
npx oh-my-skill add naveedharri/benai-skills/ads
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- naveedharri/benai-skills/ads
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify naveedharri/benai-skills/ads
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
37GitHub stars
~1.9K最小装载
~28.3K含声明引用
~28.3K文本包总量
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怎么用

技能原文 SKILL.md作者撰写 · MIT · 946a3d7

Ads — Multi-Platform Paid Advertising Audit & Optimization

Comprehensive ad account analysis across all major platforms (Google, Meta, LinkedIn, TikTok, Microsoft). Orchestrates 11 specialized sub-skills and 6 subagents.

Quick Reference

| 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 competitor | Competitor ad intelligence analysis | | /ads creative | Cross-platform creative quality audit + brand context setup + creative generation |

Orchestration Logic

When the user invokes /ads audit, delegate to subagents in parallel:

  1. Collect account data (exports, screenshots, or API access details)
  2. Detect business type and identify active platforms
  3. Spawn subagents: audit-google, audit-meta, audit-creative, audit-tracking, audit-budget, audit-compliance
  4. Collect results and generate unified report with Ads Health Score (0-100)
  5. Create prioritized action plan with Quick Wins

For individual commands (/ads google, /ads meta, etc.), load the relevant sub-skill directly.

Industry Detection

Detect business type from ad account signals:

  • SaaS: trial_start/demo_request events, pricing page targeting, long attribution windows
  • E-commerce: purchase events, product catalog/feed, Shopping/PMax campaigns
  • Local Service: call extensions, location targeting, store visits, directions events
  • B2B Enterprise: LinkedIn Ads active, ABM lists, high CPA tolerance ($50+), long sales cycle
  • Info Products: webinar/course funnels, lead gen forms, low-ticket offers
  • Mobile App: app install campaigns, in-app events, deep linking
  • Real Estate: listing feeds, property-specific landing pages, geo-heavy targeting
  • Healthcare: HIPAA compliance flags, healthcare-specific ad policies
  • Finance: Special Ad Categories declared, financial products compliance
  • Agency: multiple client accounts, white-label reporting needs
Brand Context

Brand context personalizes creative briefs, ad copy, and audit recommendations.

Detection: ./branding.md in the project root.

How it gets created: When you run /ads creative, it checks for ./branding.md. If not found, it collects brand info (name, colors, voice, audience, CTAs) and creates the file before proceeding with the audit. All other ads sub-skills can then reference it.

Brand context is optional but recommended for all commands. It is required for /ads plan creative brief generation (CREATIVE-BRIEF.md). For audits, brand consistency is advisory only (not scored).

See references/brand-context.md for the full branding.md format specification.

Quality Gates

Hard rules — never violate these:

  • Never recommend Broad Match without Smart Bidding (Google)
  • 3x Kill Rule: flag any ad group/campaign with CPA >3x target for pause
  • Budget sufficiency: Meta ≥5x CPA per ad set, TikTok ≥50x CPA per ad group
  • Learning phase: never recommend edits during active learning phase
  • Compliance: always check Special Ad Categories for housing/employment/credit/finance
  • Creative: never run silent video ads on TikTok (sound-on platform)
  • Attribution: default to 7-day click / 1-day view (Meta), data-driven (Google)
  • Attribution overlap: if 2+ platforms active, run cross-platform attribution checks (XP-01 to XP-06)
Data Quality Gates

Before scoring any platform, validate data sufficiency. If thresholds are not met, display a warning and flag the score with an asterisk (*).

| Platform | Minimum Data | Minimum Conversions | Minimum Spend | |----------|-------------|--------------------| --------------| | Google Ads | 30 days | ≥15 conversions/30d for bidding checks | Active spend | | Meta Ads | 30 days | ≥50 conversions/week for learning checks | Active spend | | LinkedIn Ads | 30 days | ≥15 conversions/month | ≥$50/day | | TikTok Ads | 30 days | ≥50 conversions/week per ad group | ≥$50/day campaign | | Microsoft Ads | 30 days | ≥10 conversions/30d | Active spend |

If insufficient data:

  1. Display warning: "⚠️ Data Quality: [Platform] has [X] days of data with [Y] conversions. Score marked with * — re-audit after 30+ days."
  2. Mark affected scores with asterisk (e.g., "Google Ads: 72*/100")
  3. Proceed with audit but caveat bidding/learning phase checks as unreliable
  4. Never mark a check as FAIL solely due to insufficient data — use N/A instead
Reference Files

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 thresholds
  • references/benchmarks.md — Industry benchmarks by platform (CPC, CTR, CVR, ROAS)
  • references/bidding-strategies.md — Bidding decision trees per platform
  • references/budget-allocation.md — Platform selection matrix, scaling rules, MER
  • references/platform-specs.md — Creative specifications across all platforms
  • references/conversion-tracking.md — Pixel, CAPI, EMQ, ttclid implementation
  • references/compliance.md — Regulatory requirements, ad policies, privacy
  • references/google-audit.md — 74-check Google Ads audit checklist
  • references/meta-audit.md — 46-check Meta Ads audit checklist
  • references/linkedin-audit.md — 26-check LinkedIn Ads audit checklist
  • references/tiktok-audit.md — 25-check TikTok Ads audit checklist
  • references/microsoft-audit.md — 21-check Microsoft Ads audit checklist
  • references/creative-volume.md — Per-platform creative volume, refresh cadence, production benchmarks
  • references/brand-context.md — Brand.md format specification and integration guide
Scoring Methodology
Ads Health Score (0-100)

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)
Grading

| 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 |

Priority Levels
  • Critical: Revenue/data loss risk (fix immediately)
  • High: Significant performance drag (fix within 7 days)
  • Medium: Optimization opportunity (fix within 30 days)
  • Low: Best practice, minor impact (backlog)
Sub-Skills

This skill orchestrates 12 specialized sub-skills:

  1. ads-audit — Full multi-platform audit with parallel delegation
  2. ads-google — Google Ads deep analysis (Search, PMax, YouTube)
  3. ads-meta — Meta Ads deep analysis (FB, IG, Advantage+)
  4. ads-youtube — YouTube Ads specific analysis
  5. ads-linkedin — LinkedIn Ads deep analysis
  6. ads-tiktok — TikTok Ads deep analysis
  7. ads-microsoft — Microsoft/Bing Ads deep analysis
  8. ads-creative — Cross-platform creative audit + brand context setup + creative generation via infographic-v2
  9. ads-landing — Landing page quality for ad campaigns
  10. ads-budget — Budget allocation and bidding strategy
  11. ads-plan — Strategic ad planning with industry templates
  12. ads-competitor — Competitor ad intelligence
Subagents

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, Microsoft
  • audit-tracking — Conversion tracking health across all platforms
  • audit-budget — Budget, bidding, structure for LinkedIn, TikTok, Microsoft
  • audit-compliance — Compliance, settings, performance across all platforms
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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