ads-meta

Meta Ads deep analysis covering Facebook and Instagram advertising. Evaluates 46 checks across Pixel/CAPI health, creative diversity and fatigue, account structure, and audience targeting. Includes Advantage+ assessment. Use when user says Meta Ads, Facebook Ads, Instagram Ads, Advantage+, or Meta campaign.

1,531 stars

Best use case

ads-meta is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Meta Ads deep analysis covering Facebook and Instagram advertising. Evaluates 46 checks across Pixel/CAPI health, creative diversity and fatigue, account structure, and audience targeting. Includes Advantage+ assessment. Use when user says Meta Ads, Facebook Ads, Instagram Ads, Advantage+, or Meta campaign.

Teams using ads-meta should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/ads-meta/SKILL.md --create-dirs "https://raw.githubusercontent.com/AgriciDaniel/claude-ads/main/skills/ads-meta/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/ads-meta/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How ads-meta Compares

Feature / Agentads-metaStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Meta Ads deep analysis covering Facebook and Instagram advertising. Evaluates 46 checks across Pixel/CAPI health, creative diversity and fatigue, account structure, and audience targeting. Includes Advantage+ assessment. Use when user says Meta Ads, Facebook Ads, Instagram Ads, Advantage+, or Meta campaign.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Meta Ads Deep Analysis

## Process

1. Collect Meta Ads data (Ads Manager export, Events Manager screenshot, EMQ scores)
2. Read `ads/references/meta-audit.md` for full 46-check audit
3. Read `ads/references/benchmarks.md` for Meta-specific benchmarks
4. Read `ads/references/scoring-system.md` for weighted scoring
5. Evaluate all applicable checks as PASS, WARNING, or FAIL
6. Calculate Meta Ads Health Score (0-100)
7. Generate findings report with action plan

## What to Analyze

### Pixel / CAPI Health (30% weight)
- Meta Pixel installed and firing on all pages
- Conversions API (CAPI) active (30-40% data loss without it post-iOS 14.5)
- Event deduplication configured (event_id matching, ≥90% dedup rate)
- Event Match Quality (EMQ) ≥8.0 for Purchase event
- All standard events configured (ViewContent, AddToCart, Purchase, Lead)
- Custom conversions created for non-standard events
- Aggregated Event Measurement (AEM) configured for iOS
- Domain verification completed
- Server-side events include customer_information parameters
- Pixel fires with correct currency and value parameters

### Creative (30% weight)
- ≥3 creative formats active (image, video, carousel, collection)
- ≥5 creatives per ad set (Meta recommendation)
- Creative fatigue detection: CTR drop >20% over 14 days = FAIL
- Video creative: 15s max for Stories/Reels, 30s max for Feed
- UGC/testimonial creative tested
- Dynamic Creative Optimization (DCO) tested
- Ad copy: headline under 40 chars, primary text under 125 chars
- Creative refresh cadence: every 2-4 weeks for high-spend

### Account Structure (20% weight)
- Campaign Budget Optimization (CBO) vs Ad Set Budget (ABO) intentional
- Campaign consolidation: ≤5 active campaigns per objective type
- Learning phase health: <30% ad sets in "Learning Limited" (FAIL >50%)
- Budget per ad set: ≥5x target CPA (minimum for learning phase exit)
- Ad set audience overlap <30% (Audience Overlap tool)
- Campaign naming conventions consistent and descriptive
- Advantage+ Shopping Campaigns (ASC) active for e-commerce
- Simplified campaign structure (fewer, larger ad sets preferred)

### Audience & Targeting (20% weight)
- Prospecting frequency (7-day): <3.0 (WARNING 3-5, FAIL >5)
- Retargeting frequency (7-day): <8.0 (WARNING 8-12, FAIL >12)
- Custom Audiences: website visitors, customer lists, engagement
- Lookalike Audiences: multiple seed sizes tested (1%, 3%, 5%)
- Advantage+ Audience tested vs manual targeting
- Interest targeting: broad enough for algorithm optimization
- Exclusions: purchasers excluded from prospecting, overlap managed
- Location targeting reviewed for relevance

## Advantage+ Assessment

If Advantage+ features are in use:
- **ASC (Shopping Campaigns)**: catalog connected, existing customer cap set
- **Advantage+ Audience**: performance vs manual audience compared
- **Advantage+ Creative**: enhancements enabled (text, brightness, music)
- **Advantage+ Placements**: enabled (let Meta optimize placement mix)
- **Budget allocation**: Advantage+ campaigns getting fair test budget

## Special Ad Categories

If ads are in restricted categories:
- Special Ad Category declared before campaign creation
- Targeting restrictions verified (no ZIP, age 18-65+ only, no Lookalike)
- Creative compliance with category-specific policies
- Read `ads/references/compliance.md` for full requirements

## EMQ Optimization Guide

| EMQ Score | Status | Action |
|-----------|--------|--------|
| 8.0-10.0 | Excellent | Maintain current setup |
| 6.0-7.9 | Good | Add more customer_information parameters |
| 4.0-5.9 | Fair | Implement CAPI, improve data quality |
| <4.0 | Poor | Critical: CAPI + Enhanced Matching required |

Key parameters to maximize EMQ:
- `em` (email): highest match rate signal
- `ph` (phone): second highest match signal
- `fn`, `ln` (first/last name): improves match accuracy
- `ct`, `st`, `zp` (city, state, zip): geographic matching
- `external_id`: CRM/user ID for cross-device matching

## Key Thresholds

| Metric | Pass | Warning | Fail |
|--------|------|---------|------|
| EMQ (Purchase) | ≥8.0 | 6.0-7.9 | <6.0 |
| Dedup rate | ≥90% | 70-90% | <70% |
| CTR | ≥1.0% | 0.5-1.0% | <0.5% |
| Creative formats | ≥3 | 2 | 1 |
| Creatives per ad set | ≥5 | 3-4 | <3 |
| Learning Limited | <30% | 30-50% | >50% |
| Budget per ad set | ≥5x CPA | 2-5x CPA | <2x CPA |

## Output

### Meta Ads Health Score

```
Meta Ads Health Score: XX/100 (Grade: X)

Pixel / CAPI Health: XX/100  ████████░░  (30%)
Creative:            XX/100  ██████████  (30%)
Account Structure:   XX/100  ███████░░░  (20%)
Audience:            XX/100  █████░░░░░  (20%)
```

### Deliverables
- `META-ADS-REPORT.md`: Full 46-check findings with pass/warning/fail
- EMQ improvement roadmap
- Creative fatigue alerts (any creative with CTR declining >20%)
- Quick Wins sorted by impact
- Advantage+ adoption recommendations

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