| name | meta-reporting |
| title | Meta ads reporting |
| description | Use this skill when analyzing or reporting Meta Ads performance — pulls live Meta insights, reads them like an operator (leading vs vanity signals), and generates a shareable branded HTML dashboard.
Triggers: Meta report, Meta dashboard, Meta performance, analyze Meta ads, cost per lead, CPL report, Meta account audit, weekly Meta report, client dashboard, ad spend report.
|
| category | Ads |
Meta Ads Reporting and Dashboards
Turn raw Meta numbers into a decision. This skill pulls live performance, analyzes it against the operating system in the meta-ads skill, and renders a clean, client-ready dashboard.
What this covers
- Performance analysis - pull live spend, leads, CPL, CTR, CPM, reach at account and campaign level, then read it like an operator (leading vs vanity signals).
- Reporting - weekly or period-over-period rollups: what changed, what is working, what to fix first.
- Dashboards - a self-contained HTML dashboard branded with the Frontal logo, that you open in a browser or send to a client.
Scripts
Run from .claude/skills/meta-ads/scripts/ (shared client + .env) unless noted.
| Task | Command |
|---|
| Account snapshot (all KPIs, one call) | python account_overview.py |
| Campaign performance table | python get_campaign_performance.py --date-preset last_30d |
| Pull active ad copy (for a creative/audit read) | python get_active_ads_copy.py |
| Branded HTML dashboard | cd ../../meta-reporting/scripts && python generate_dashboard.py --date-preset last_30d |
The dashboard (with your logo)
generate_dashboard.py writes a shareable HTML file: KPI tiles (spend, leads, cost per lead, CTR, CPM, reach) plus a per-campaign table, sorted by spend.
cd .claude/skills/meta-reporting/scripts
python generate_dashboard.py
python generate_dashboard.py --date-preset last_7d --out weekly.html
It ships with the Frontal logo by default. It's your dashboard - rebrand it:
- Set
DASHBOARD_LOGO_URL and DASHBOARD_BRAND_NAME in .env, or
- Pass
--logo https://yourbrand.com/logo.png --brand "Your Brand".
No image API, no external service - just the Meta API and Python. Open it with open meta-dashboard.html or attach the file to an email.
How to analyze (not just report)
Reporting is describing the numbers. Analysis is deciding what to do. Always:
- Lead with the outcome metric, not vanity. Cost per lead and lead volume first. Impressions, reach, and CPM are context, never the headline. (See
ads-foundations/measurement-scorecard.md.)
- Separate leading from lagging signals. CTR and CPM move first; CPL and lead volume confirm. A rising CPM with flat CPL is fine; a rising CPL is the alarm.
- Read at the right altitude. Account -> campaign -> ad set -> ad. Find the level where the money is leaking before recommending a fix.
- Tie every number to an action. "CPL up 40% week over week, driven by the retargeting campaign fatiguing (frequency 4.2). Action: rotate creative, cap frequency." Not "CPL went up."
- Never fabricate a benchmark. If you do not have the account's own history, say so. Use the B2B benchmarks in
meta-ads/knowledge-base/optimization-playbook.md as reference ranges, labeled as such.
Output standards
- Dashboards are client-ready: clean, branded, no jargon, no source citations.
- Written reports lead with wins, then concerns, with week-over-week numbers at the campaign level.
- Follow
ads-foundations/writing-style.md for everything you write. No AI slop, no em dashes, no emoji.
