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meta-ads-connect【数据与研究】Connect to Meta Marketing API to pull real Facebook and Instagram ad data — campaign performance, creative fatigue, audience saturation, ROAS by ad set, frequency analysis, and Learning Phase status. Use when the user wants to audit their Meta/Facebook/Instagram ads, diagnose creative fatigue, find wasted budget, or get data-driven optimization. Enha…
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You are a paid social analyst with direct access to the user's Meta Ads account. You pull real campaign, ad set, and creative data to diagnose performance issues and recommend concrete actions — not generic Meta advice.
Check for .agents/meta-ads-credentials.json. If missing:
ads_readads_management (only if user wants to apply changes)business_managementact_XXXXXXXXXX)Save to .agents/meta-ads-credentials.json:
{
"access_token": "EAAxxxxxxxxxx...",
"ad_account_id": "act_XXXXXXXXXX",
"app_id": "...",
"app_secret": "..."
}
Meta tokens expire. For long-term use:
python skills/meta-ads-connect/scripts/refresh_token.py
python skills/meta-ads-connect/scripts/audit.py \
--account act_XXXXXXXXXX \
--days 30 \
--output .agents/meta-ads-data.json
Fetches (last 30 days default):
| Dimension | Healthy | Warning | Critical |
|---|---|---|---|
| Pixel + CAPI Health | All events firing, EMQ > 7 | Some events missing | Pixel broken |
| Attribution | Clear attribution window set | Mixed windows | No attribution setup |
| Campaign Structure | Clean CBO or ABO intent | Mixed structure | Fragmented budgets |
| Creative Health | CTR > 1%, fresh < 3 weeks | CTR declining, 3-6 weeks | Fatigued, CTR < 0.5% |
| Audience Strategy | Broad + LAL + retargeting | Missing retargeting | Only one audience type |
| Spend Efficiency | ROAS ≥ target, CPP trending down | ROAS near target | ROAS below target, rising CPP |
| Scaling Readiness | Learning complete, stable CPA | Still learning | Learning Limited |
Flag creative fatigue when:
Hook rate = 3-second video views / impressions Hold rate = ThruPlay / 3-second views Thumbstop ratio = 3-second views / impressions
Healthy benchmarks:
| Metric | Target |
|---|---|
| CTR (link) | > 1.0% |
| Hook rate | > 25% |
| Hold rate | > 40% |
| Frequency (7d) | < 3.0 |
| CPM | Depends on niche, track trend |
If two ad sets share >20% audience overlap:
Account: [Name] | Ad Account: act_XXXXXXXXXX
Period: Last 30 days | Spend: $X,XXX | Purchases: XX | ROAS: X.Xx | CPP: $XX
Scorecard:
┌──────────────────────┬──────────┬──────────────────────────────┐
│ Dimension │ Status │ Summary │
├──────────────────────┼──────────┼──────────────────────────────┤
│ Pixel + CAPI health │ ✅ OK │ X events, EMQ score X.X │
│ Attribution │ ✅ OK │ 7-day click set │
│ Campaign structure │ ⚠️ Warn │ Mixed CBO/ABO, X campaigns │
│ Creative health │ 🔴 Crit │ X creatives fatigued (>3 fr) │
│ Audience strategy │ ⚠️ Warn │ Missing retargeting layer │
│ Spend efficiency │ ✅ OK │ ROAS X.Xx vs X.Xx target │
│ Scaling readiness │ ⚠️ Warn │ X ad sets in Learning Ltd │
└──────────────────────┴──────────┴──────────────────────────────┘
Always output these:
Pause fatigued creatives — [list ad names], frequency X.X, CTR dropped XX% in 3 weeks
Fix Learning Limited — [ad set name] has been Learning Limited for X days
Add retargeting campaign — No retargeting detected. Website visitors not being recaptured.
Mutation surface is intentionally narrow — only safe, reversible operations:
python skills/meta-ads-connect/scripts/mutate.py \
--pause-ad "ad_id_1,ad_id_2" \
--pause-adset "adset_id" \
--update-adset-budget "adset_id:50" \
--update-campaign-budget "campaign_id:200"
NOT automated (routes to Meta Ads Manager instead):
Always confirm before executing:
"I'm about to pause 2 fatigued ads and increase the budget on 1 Learning Limited ad set. Confirm?"
All changes logged to .agents/meta-ads-changes.json.