Morning Brief

Meta Ads Morning Brief

Produce a daily, prioritized account-health narrative for Meta Ads (Facebook + Instagram) with actionable items, dollar-quantified anomalies, and UI paths for every fix.

Account Context

Read ${CLAUDE_PLUGIN_ROOT}/profile/account-profile.md at the start of every run. If it exists:

• Use known account IDs — skip get_ad_accounts discovery.
• Apply KPI targets as anomaly detection thresholds (e.g., flag CPA > target CPA, CPM > ceiling).
• Use frequency cap from profile to calibrate fatigue alerts.
• Note active creative/audience tests when interpreting performance shifts.
• Check watch list for follow-up items from prior sessions. If it doesn't exist, fall back to mcp__meta-ads__get_ad_accounts and suggest running platform-setup.

Key Metrics

Workflow

Phase 1: Collect data

1. Campaign performance (today vs 7d vs 30d): Use mcp__meta-ads__list_campaigns to get all active campaigns. Use mcp__meta-ads__get_campaign_performance for each campaign with yesterday, 7d, and 30d windows. Metrics: spend, impressions, CPM, clicks, CTR, conversions, CPA, ROAS, frequency.

2. Ad set delivery status: Use mcp__meta-ads__list_ad_sets for each campaign. Flag: Learning Limited, Delivery Issue, or any non-Active delivery status.

3. Period comparison: Use mcp__meta-ads__compare_performance for week-over-week and month-over-month trends.

4. Account-level insights: Use mcp__meta-ads__get_insights for account-level aggregated performance.

Phase 2: Detect anomalies

For each metric, compare yesterday vs 7d baseline:

deviation_pct = (yesterday - avg_7d) / avg_7d
dollar_impact = (yesterday_metric - avg_7d_metric) * yesterday_volume

Flag when |deviation_pct| > 0.20 AND |dollar_impact| > $10.

Meta-specific flags:

• Learning Limited: Any ad set stuck in Learning Limited delivery status.
• Frequency spike: Any ad set with 7d frequency > 3.0.
• CPM spike without audience change: Suggests creative fatigue or auction competition.
• Delivery issues: Ad sets with delivery problems (budget constraints, audience too small, billing issues).

Assign severity:

• HIGH (>$500/mo projected impact): Broken campaigns, Learning Limited on high-spend ad sets, CPM spikes on primary campaigns.
• MEDIUM ($100-500/mo): Frequency violations, declining CTR, budget pacing issues.
• LOW ($25-100/mo): Minor metric shifts, low-spend anomalies.
• INFO (<$25/mo): Informational observations.

Phase 3: Budget pacing

For campaigns with daily budgets:

daily_pacing = yesterday_spend / daily_budget

• Flag overpacing: >1.10 (spending faster than expected).
• Flag underpacing: <0.85 (delivery issues or audience saturation).

For campaigns with lifetime budgets:

days_remaining = end_date - today
remaining_budget = lifetime_budget - total_spend
ideal_daily = remaining_budget / days_remaining
actual_daily = avg_spend_last_3d
pacing_ratio = actual_daily / ideal_daily

• Flag overpacing: >1.20 (will exhaust budget early).
• Flag underpacing: <0.80 (will underspend).

Phase 4: Draft prioritized narrative

Structure output by priority, not by campaign.

Output Format

## Morning Brief - [Date]

### Account Summary
| Metric | Yesterday | 7d Avg | 30d Avg | Trend |
|--------|----------:|-------:|--------:|-------|
| Spend | | | | |
| CPM | | | | |
| CTR | | | | |
| CPA | | | | |
| ROAS | | | | |
| Conversions | | | | |

### Urgent [HIGH]
> Items requiring action today. Each with dollar impact and fix path.

**[Finding title]** — [SEVERITY]
- Impact: $X/mo estimated waste
- Signal: [what triggered the flag]
- Fix: Meta Ads Manager > [exact UI path]
- [Copy-paste artifact if applicable]

### Watch [MEDIUM]
> Monitor — act if trend continues 48 hours.

### Healthy
> Campaigns performing at or above targets.

| Campaign | Objective | Spend | CPA | ROAS | Status |
|----------|-----------|------:|----:|-----:|--------|

### Budget Pacing
| Campaign | Type | Budget | Spend | Pacing | Status |
|----------|------|-------:|------:|-------:|--------|

### Notes
- Attribution: 7-day click / 1-day view (flag if account uses different).
- iOS ATT: Note potential underreporting from opt-outs.
- Learning phase: Campaigns in learning phase are excluded from anomaly flags.

Guardrails

• Learning phase: Do NOT flag campaigns in learning phase (<50 conversions/week) as underperforming. Note them separately.
• Attribution window: Always note Meta's default 7-day click / 1-day view window. Flag if account uses a different window.
• iOS privacy: Note potential underreporting from ATT opt-outs when conversion numbers seem low.
• Seasonality: Check if today is a known high/low spending day (weekend, holiday, etc.) before flagging pacing anomalies.
• Read-only: This skill produces analysis only. All recommended actions include UI paths — no mutations.

Profile Maintenance

After completing analysis, if ${CLAUDE_PLUGIN_ROOT}/profile/account-profile.md exists:

1. Update Watch List with any new anomalies flagged in this run.
2. Update Active Tests if user mentioned starting or completing a test.
3. Append to Decision Log if actions were taken.
4. Update "Last updated" date. Present proposed profile changes to the user before writing.

References

• references/thresholds.md — Anomaly detection thresholds
• references/benchmarks.md — 2026 Meta benchmarks by objective and vertical
• references/ui-paths.md — Meta Ads Manager UI paths for every action