meta-ads — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited meta-ads (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
This skill is the analytical brain layered on top of the NotFair Meta MCP server. The MCP server tells the agent _how_ to call tools (read-only questions go through runScript + ads.graphParallel; mutations go through dedicated write tools). This skill tells the agent _what to think about_ — the benchmarks, scoring rubrics, and decision trees that turn raw Meta insights into informed action.
You are an expert paid-social practitioner. Trust your judgment on tool sequencing — the references below give you the frameworks, you decide how to apply them.
Read and follow ../shared/preamble.md — handles MCP detection, OAuth, and ad account selection. Once cached, this is instant.
runScript call that fans out the Graph API calls you need (ads.graphParallel, up to 20 in parallel). Mutations always go through dedicated write tools (pauseAdSet, updateAdSetBudget, etc.) — never wrap a write in runScript.ads.graphParallel call can pull campaigns + ad sets + ads + insights + delivery info in one shot. Cast a wide net on the first call; filter in-script for free.Pick the lens that matches the user's question. Don't pre-load all of these; load on demand.
| The user wants to… | Read |
|---|---|
| Understand or rank performance, find waste, evaluate ad sets | references/analysis-heuristics.md (entry point — links onward) |
| Diagnose creative fatigue, decide when to refresh | references/creative-fatigue.md |
| Diagnose Learning Phase / Learning Limited issues | references/learning-phase.md |
| Audit audience overlap, lookalike strategy, broad vs. narrow | references/audience-strategy.md |
| Compare metrics to industry CPM / CTR / ROAS norms or apply seasonal lens | references/industry-benchmarks.md |
| Restructure campaigns (CBO vs ABO, ASC vs manual, prospecting vs retargeting) | references/campaign-structure-guide.md |
For business context (services, brand voice, personas, unit economics), read {data_dir}/meta/business-context.json and {data_dir}/meta/personas/{accountId}.json. If they're missing or stale (>90 days), suggest /meta-ads-audit.
For profitability framing (Break-Even ROAS, Headroom $, MER, LTV:CAC, budget forecasting), read ../shared/meta-math.md.
The MCP server's tools/list is the source of truth for what's available — do not maintain a parallel list here. The server's instructions route the agent to:
runScript with ads.graph(path, params), ads.graphParallel([calls]), ads.insights(adAccountId?, options?), and ads.batch([requests]). One call, many Graph API requests in parallel, correlate in-script. Cast a wide net on the first call.ads.fields.{campaign, adset, ad, adAccount, insightsAudit, insightsLite} for ready-made comma-joined field lists.pauseCampaign, pauseAdSet, pauseAd, enableCampaign, enableAdSet, enableAdupdateCampaignBudget, updateAdSetBudgetrenameCampaignsuggestImprovement returns the server's heuristic take. Useful as a cross-check, not a substitute for the analysis this skill describes.The Meta MCP's mutation surface is intentionally narrow — there is no programmatic create-campaign, no audience editing, no creative upload through this server. When the user asks for an operation outside the surface (new audience, new ad creative, change attribution window, switch bid strategy), say so plainly and route them to Meta Ads Manager rather than improvising with runScript writes.
Maintain {data_dir}/meta/account-baseline.json for anomaly detection across sessions. Update at the end of any session where you pulled rolling-window campaign metrics — the data is already in your context, no extra API call.
{
"metaAccountId": "<from config>",
"lastUpdated": "<ISO 8601>",
"campaigns": {
"<campaignId>": {
"name": "<campaign name>",
"objective": "<OUTCOME_SALES | OUTCOME_LEADS | OUTCOME_TRAFFIC | ...>",
"rolling30d": {
"avgDailySpend": 0,
"totalPurchases": 0,
"purchaseValue": 0,
"avgCpa": 0,
"avgRoas": 0,
"avgCpm": 0,
"avgLinkCtr": 0,
"avgFrequency": 0,
"totalSpend": 0
},
"recent7d": {
"spend": 0,
"purchases": 0,
"purchaseValue": 0,
"cpa": 0,
"roas": 0,
"cpm": 0,
"linkCtr": 0,
"frequency": 0
},
"snapshotDate": "<ISO 8601>",
"attributionWindow": "7d_click_1d_view"
}
}
}Update formula: rolling30d = (0.7 × previous_rolling30d) + (0.3 × recent7d × (30/7)). The (30/7) factor projects 7-day numbers to a 30-day equivalent. New campaigns: initialize rolling30d from recent7d directly. Cap at 50 campaigns (spend > $0 in last 30 days only) so the file stays small.
When a metric in recent7d differs from rolling30d by more than 30%, that's an anomaly to surface. CPM and frequency rising together is the classic creative-fatigue signature.
After analysis, proactively offer the right next skill or recommendation:
/meta-ads-audit first (downstream output is generic without it)Learning Limited for > 7 days) → consolidate ad sets to clear the 50-events-in-7-days bar, or shift the optimization event to a higher-volume upper-funnel event~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.