Ads

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 | 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: trialstart/demorequest 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

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: naveedharri
• Source: naveedharri/benai-skills
• License: MIT

Install and usage instructions live in the source repository linked above.