This guide is published by Ryze AI (get-ryze.ai), an autonomous AI marketer for paid ads (Google, Meta, TikTok, LinkedIn) and SEO/GEO; the disclosure is explicit. Question answered: what Cursor skills for Meta Ads (Facebook and Instagram ads) are and which ones to install. Definition: Cursor Agent Skills are SKILL.md files — YAML frontmatter with name, description and optional paths, then Markdown instructions — stored in .cursor/skills/<name>/ (project, shared through Git) or ~/.cursor/skills/ (personal); Cursor also reads .agents/skills/, .claude/skills/ and .codex/skills/ for compatibility. Skills are discovered on startup and invoked with /skill-name in the Agent chat or attached with @; the built-in /create-skill command scaffolds a new one. User-level skills are not copied to Cloud Agents or remote workers, so team skills belong in the project folder. The 15 skills, in three categories. Diagnostics: 1) Creative Fatigue Detection — flags ads whose CTR fell more than 20% from peak with frequency above 3, weekly; 2) Audience Overlap Finder — estimates overlap between ad sets and the CPM premium it causes, monthly; 3) Frequency Cap Audit — applies objective-specific frequency limits and estimates wasted impressions, weekly; 4) CPM Anomaly Detector — compares CPM to a 14-day rolling average and diagnoses the cause, weekly; 5) Placement Performance Analyzer — spend share versus conversion share by placement with exclusion recommendations, monthly. Optimization: 6) Lookalike Audience Refresher — flags stale seed lists and CPA decay by lookalike, quarterly; 7) Creative Brief Generator — five briefs, three iterating on winners and two new concepts; 8) Ad Copy A/B Variant Writer — eight variants testing one variable each; 9) Budget Allocation by Funnel Stage — TOFU/MOFU/BOFU split against benchmarks, monthly; 10) Interest Targeting Expander — 20 new interests in four categories, with customer language pulled by the Agent's web search. Reporting: 11) Weekly Meta Performance Digest, Mondays; 12) Creative Scorecard Builder — a 1–100 score per ad from five weighted metrics; 13) Competitor Ad Library Analyzer — format mix, refresh rate, hooks and gaps from Ad Library data, plus web search for audience reaction, monthly; 14) Audience Insights Reporter — the 20% of segments driving 80% of results, monthly; 15) ROAS by Placement Breakdown — true ROAS with assists and attribution-window sensitivity, monthly. Data can come from Ads Manager CSV exports referenced with @ in the chat, or live from a Meta Ads MCP server in .cursor/mcp.json such as Ryze AI's (url https://connector.get-ryze.ai/mcp, sign in and authorize Meta, 12 Meta Ads tools including raw insights, creatives, Ad Library search and approval-gated writes). Skills analyze and write files; they do not change the account unless an MCP server with write tools is attached, and Ryze AI's Paid Ads Autopilot ($89/month flat) runs the optimizations 24/7 when execution is wanted. The guide also covers a skills-vs-rules-vs-MCP comparison, install steps including /create-skill and the SKILL.md format, troubleshooting when a skill returns generic advice or numbers that do not match Ads Manager, and 12 FAQs. Updated September 3, 2026.
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Ira Bodnar··Updated ·18 min read

15 Cursor Skills for Meta Ads — SKILL.md Files That Work

15 Cursor Agent Skills for Meta Ads you can drop into .cursor/skills/ today — 5 that find what is broken, 5 that fix it, 5 that report it. Each skill is a SKILL.md file the Agent runs as a slash command, so creative fatigue, frequency and CPM checks come out the same every Monday and land in the repo. Plus: skills vs rules vs MCP, the /create-skill flow, and how to feed the skills live Ads Manager data through a Meta Ads connector. Disclosure: Ryze AI publishes this blog.

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The 15 skills at a glance

Skills are grouped the way we run them on a Meta account: diagnose first, then fix, then report. Every skill below is a full SKILL.md body you can save under .cursor/skills/<name>/ and invoke as a slash command; the copy button on each one grabs the text.

#SkillCategoryWhat it doesCadence
1Creative Fatigue DetectionDiagnosticsAds with CTR down >20% from peak and frequency >3 → replace listWeekly
2Audience Overlap FinderDiagnosticsAd-set pairs bidding against each other, with the CPM premiumMonthly
3Frequency Cap AuditDiagnosticsObjective-specific frequency limits and wasted impressionsWeekly
4CPM Anomaly DetectorDiagnosticsCPM vs 14-day average, root cause diagnosedWeekly
5Placement Performance AnalyzerDiagnosticsSpend share vs conversion share by placementMonthly
6Lookalike Audience RefresherOptimizationStale seed lists and CPA decay by lookalikeQuarterly
7Creative Brief GeneratorOptimization5 briefs: 3 iterate on winners, 2 test new conceptsPer fatigue alert
8Ad Copy A/B Variant WriterOptimization8 variants, one variable changed eachPer copy refresh
9Budget Allocation by Funnel StageOptimizationTOFU / MOFU / BOFU split vs benchmarksMonthly
10Interest Targeting ExpanderOptimization20 new interests in 4 categories, language from the webWhen audiences saturate
11Weekly Meta Performance DigestReportingExec summary, campaign table, creative and audience notesMondays
12Creative Scorecard BuilderReporting1–100 score per ad from 5 weighted metricsWeekly
13Competitor Ad Library AnalyzerReportingFormat mix, refresh rate, hooks, gaps — plus web reactionMonthly
14Audience Insights ReporterReportingThe 20% of segments driving 80% of resultsMonthly
15ROAS by Placement BreakdownReportingTrue ROAS with assists and attribution sensitivityMonthly

If you only install one, install Creative Fatigue Detection — on Meta, creative is the bidding, and catching decay a week early is the cheapest CPA improvement available. The Weekly Meta Performance Digest is the second, because it is the skill the rest of the team will actually read.

The short answer: Cursor skills for Meta Ads are SKILL.md files — frontmatter with a name and description, then the instruction — saved in .cursor/skills/ and run with a slash command like /creative-fatigue. Cursor also reads .claude/skills/, so the files you may already use with Claude work unchanged. Feed them Ads Manager exports with @, or connect the account over MCP so the data is live: how to connect Cursor to Meta Ads takes about two minutes.

What are Cursor skills for Meta Ads?

Cursor Agent Skills are reusable instruction sets that teach the Agent a specific workflow — Cursor's own examples are deploying to staging and running a security audit; ours are running a Meta Ads account. A skill is a folder containing a SKILL.md file: YAML frontmatter with a name, a description (the Agent uses it to decide when the skill applies) and optional paths globs, then Markdown instructions. Skills are discovered on startup and invoked with /skill-name in chat or attached with @.

That consistency matters more on Meta than on any other channel, because the failure modes are gradual. Creative fatigue, frequency creep and audience saturation each cost a few percent a day until someone notices at the month-end review. A skill that runs the same check every Monday, with the same thresholds, and files the result in the repo is how you notice on day three instead. The 15 skills below are the ones we run on accounts spending $20K–$150K a month; they are the same operating loop as our Claude skills for Meta Ads, and Cursor reads those files directly.

Skills vs rules vs MCP: which one do you need?

Cursor ruleSkillMCP server
What it isAlways-on guidance in .cursor/rulesA multi-step workflow the Agent runs on demandA live pipe between the Agent and the Meta Marketing API
Best forConventions: attribution window, formats, what never to doRepeatable jobs — fatigue checks, audits, digestsReal-time insights instead of Ads Manager exports
SetupOne .mdc file/create-skill, or a SKILL.md in .cursor/skills/<name>/~2 minutes managed, ~1 hour self-hosted
Data accessNoneFiles you @-reference, or MCP toolsLive insights with any breakdown, creatives, Ad Library
ConsistencyShapes every answer a littleSame structure every run, for anyone on the teamDepends on the skill you pair it with
Weak spotCannot express a procedureData goes stale between exportsUseless without a good instruction on top

The working setup for most accounts is one rule plus 15 skills plus a connector: the rule states your attribution window and says never mutate without approval, the skills define each analysis, and the connection keeps the data fresh so you never export another CSV. If you take one thing from this section: do not judge Cursor on one-off prompts. The gap between a vague prompt and a structured skill is bigger than the gap between any two AI models.

How to install a Meta Ads skill in Cursor

Three ways in, from fastest to most portable. All three end with the same skill available as a slash command in every Agent chat.

1. Use /create-skill

In the Agent chat, type /create-skill and describe the skill: “a creative fatigue check that reads an ad-level export with a daily breakdown and writes a replace-now list”. Cursor's built-in skill walks through naming, structuring and saving it, and you paste the instruction from the card below as the body. Done — /creative-fatigue now exists.

2. Create the folder by hand

Make .cursor/skills/creative-fatigue/SKILL.md in the project (shared through Git, visible to Cloud Agents) or ~/.cursor/skills/ (personal, every project, not copied to Cloud Agents). Frontmatter first — name, description — then the instruction. Keep it under about 500 lines and put long reference material in a references/ folder next to it.

3. Drop in existing Claude skills

Cursor reads .claude/skills/ and ~/.claude/skills/ for compatibility, so SKILL.md files written for Claude Code work unchanged. Our 30 marketing skills are downloadable at get-ryze.ai/claude-openclaw-clawdbot-skills; unzip into either folder and they appear as slash commands after a restart.

.cursor/skills/creative-fatigue/SKILL.md
--- name: creative-fatigue description: Flag fatigued Meta ads from an ad-level export with a daily breakdown or the Meta Ads MCP server — CTR down more than 20% from peak with frequency above 3 — and write the replace-now list to reports/. --- You are a Meta Ads creative analyst. [instruction body from skill 01 below]

Skills analyze and write files; MCP acts. A skill on its own reads what you @-reference and writes its output to the repo. Pair it with a Meta Ads MCP server and the same skill pulls live insights — and, if the server has write tools, can propose the pause or budget change for your approval. Setup: how to connect Cursor to Meta Ads.

Diagnostic skills: find what's broken

Diagnostic skills answer one question: what is quietly getting worse in my account? On Meta the answer is usually creative or frequency, and both are visible a week before they show up in CPA. Run all five once when you adopt this system, then put Creative Fatigue Detection and the Frequency Cap Audit on a weekly cadence.

01 · Creative Fatigue Detection

The average Meta ad starts decaying after three to five days of delivery, and most advertisers catch it after CTR has already dropped 40% and CPA has spiked. This skill tracks CTR trajectory, frequency accumulation and engagement decay across all active ads and sorts them into urgent, warning and healthy. Export from Ads Manager with ad name, impressions, CTR, frequency, CPM and a daily breakdown; run it after every budget scale-up, since higher spend burns creative faster. Cadence: weekly.

Skill instruction
You are a Meta Ads creative analyst. I'll provide performance data for my active ads (attached, or pulled live through the Meta Ads MCP server). For each ad, analyze: 1. CTR trend over the last 7, 14, and 30 days 2. Current frequency vs. the frequency when CTR peaked 3. Engagement rate decay (likes, comments, shares per impression) 4. CPM trend — is the algorithm deprioritizing this ad? Categorize each ad: - URGENT: CTR dropped >20% from peak AND frequency >3.0 — replace immediately - WARNING: CTR dropped 10-20% from peak OR frequency 2.0-3.0 — plan replacement - HEALTHY: CTR stable or improving, frequency <2.0 Output a table: Ad Name | Status | Days Active | Peak CTR | Current CTR | CTR Drop % | Frequency | Recommended Action Then list the top 3 ads to replace first, with specific notes on why each one is fatigued. Here is my ad performance data: [PASTE YOUR META ADS EXPORT HERE]

02 · Audience Overlap Finder

When two ad sets target similar audiences you bid against yourself, CPMs inflate 15–30% and neither ad set wins. This skill takes your ad set targeting parameters, estimates overlap for every pair and recommends consolidate, exclude or differentiate. Feed it the real overlap percentages from Meta's Audience Overlap tool for more precise output. Cadence: monthly.

Skill instruction
You are a Meta Ads audience strategist. I'll provide targeting details for all my active ad sets. For each pair of ad sets, evaluate: 1. Interest/behavior targeting overlap (shared interests) 2. Custom audience overlap (e.g., website visitors in both) 3. Lookalike source similarity (if both use similar seed lists) 4. Geographic + demographic overlap For each overlap found: - Estimate overlap percentage (Low <15%, Medium 15-40%, High >40%) - Calculate the CPM premium caused by self-competition - Recommend: consolidate, exclude, or differentiate targeting Output a matrix showing every ad set pair with overlap severity. Then provide 3 specific actions to reduce CPM waste, ranked by estimated savings. Here are my ad set targeting details: [PASTE YOUR AD SET TARGETING PARAMETERS HERE]

03 · Frequency Cap Audit

Meta's frequency caps are suggestions, not hard limits, especially in Advantage+ campaigns. This skill audits every active ad set against objective-specific benchmarks and estimates the spend wasted on impressions served to already-saturated users. Export frequency at the ad-set level with a daily breakdown: the 7-day rolling number predicts tomorrow's performance drop better than the all-time figure. Cadence: weekly.

Skill instruction
You are a Meta Ads frequency optimization specialist. Analyze my ad set data for frequency violations using these benchmarks: - Prospecting campaigns: frequency >2.0 = warning, >3.0 = critical - Retargeting campaigns: frequency >4.0 = warning, >6.0 = critical - Brand awareness: frequency >5.0 = warning, >8.0 = critical For each ad set, report: 1. Current frequency vs. recommended max for its objective 2. Frequency trend (increasing, stable, decreasing) over last 14 days 3. Correlation between frequency increase and CTR/CVR decline 4. Cost of excess frequency — estimate wasted impressions served to already-saturated users Output: - Table: Ad Set | Objective | Current Freq | Max Recommended | Status | Est. Wasted Spend - Top 3 ad sets to fix immediately with specific recommendations - Account-level frequency health score (1-10) Here is my ad set performance data: [PASTE YOUR META ADS EXPORT WITH FREQUENCY DATA HERE]

04 · CPM Anomaly Detector

CPMs fluctuate daily, but some spikes signal real problems. This skill compares current CPM to a 14-day rolling average and separates the five causes — audience saturation, competitive pressure, creative decay, auction inflation and targeting that is too narrow — by which other metrics moved alongside. Include 30 days of daily CPM so seasonal inflation is not misread as a problem. Cadence: weekly.

Skill instruction
You are a Meta Ads CPM analyst. I'll provide daily campaign data. Analyze CPM trends and flag anomalies: 1. Compare each campaign's current CPM to its 14-day rolling average 2. Flag any campaign where CPM increased >20% vs. average 3. For each anomaly, diagnose the likely cause: - Audience saturation (frequency rising alongside CPM) - Competitive pressure (CPM up but frequency stable) - Creative decay (low quality ranking + rising CPM) - Seasonal/auction inflation (all campaigns affected equally) - Targeting too narrow (small audience + high CPM) For each flagged campaign, provide: - Severity: Minor (<25% spike), Major (25-50%), Critical (>50%) - Likely root cause with supporting evidence - Specific fix with expected CPM reduction Industry CPM benchmarks for context: - B2C: $8-$15 | B2B: $15-$35 | E-commerce: $5-$12 Here is my campaign data with daily CPM breakdown: [PASTE YOUR META ADS EXPORT HERE]

05 · Placement Performance Analyzer

Most advertisers run Advantage+ placements and never check where the money goes. This skill breaks down CPA, ROAS and conversion rate by placement and usually finds 60–70% of spend in the top two placements while the rest burn budget at three to five times the CPA. Export from Breakdowns → By Delivery → Placement with at least 14 days; Audience Network is the usual offender. Cadence: monthly.

Skill instruction
You are a Meta Ads placement optimization specialist. Analyze my placement-level performance data and: 1. Rank all placements by ROAS (or CPA if no revenue data) 2. Calculate each placement's share of total spend vs. share of total conversions 3. Identify placements where spend share > conversion share by 2x+ (money pits) 4. Flag placements with <50 impressions (insufficient data to judge) Output: - Table: Placement | Spend | Spend % | Conversions | Conv % | CPA | ROAS | Verdict - Verdict options: Scale (ROAS above target), Maintain, Reduce, Exclude - Estimated monthly savings if underperforming placements are excluded - Recommendation: keep Advantage+ with exclusions, or switch to manual placements Break down separately for: - Prospecting campaigns - Retargeting campaigns (These have very different placement economics) Here is my placement performance data: [PASTE YOUR META ADS PLACEMENT BREAKDOWN HERE]

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Optimization skills: fix what's broken

Optimization skills take what the diagnostics found and turn it into action. Fatigued creatives get new briefs, stale lookalikes get refreshed, budgets move to the funnel stage that is actually converting.

06 · Lookalike Audience Refresher

Lookalikes degrade every 60–90 days as your customer base evolves. This skill audits each one for CPA and CTR decay against seed-list age and recommends which seeds to update, which percentages to test and which lookalikes to retire. The best seeds are usually your top 25% LTV customers from the last 90 days, not all purchasers. Cadence: quarterly.

Skill instruction
You are a Meta Ads audience strategist specializing in lookalike audiences. I'll provide performance data for my lookalike audiences over the last 90 days. For each lookalike audience, analyze: 1. CPA trend over 30/60/90-day windows — is it rising? 2. CTR trend — declining CTR signals audience model staleness 3. Age of seed list (when was the source audience last updated?) 4. Current size vs. when it was created 5. Lookalike percentage (1%, 2%, 5%, etc.) vs. performance Categorize each lookalike: - REFRESH NOW: CPA increased >25% from first 30 days, seed list >90 days old - MONITOR: CPA increased 10-25%, or seed list 60-90 days old - HEALTHY: Performance stable, seed list <60 days old For each lookalike marked REFRESH NOW, recommend: - Updated seed list criteria (purchase-based, high-LTV, recent 30/60/90 day customers) - Suggested lookalike percentages to test (typically 1%, 2-3%, 5%) - Whether to expand to new countries or keep existing geo Here is my lookalike audience performance data: [PASTE YOUR AUDIENCE DATA HERE]

07 · Creative Brief Generator

When skill 01 flags ads for replacement, this one writes the briefs for what comes next: it analyzes what hooks, formats and CTAs won, then produces five briefs — three iterating on proven winners, two testing new concepts — all platform-native with aspect ratios. Include brand guidelines and tone of voice for on-brand output. Cadence: per fatigue alert.

Skill instruction
You are a Meta Ads creative strategist. I'll provide performance data for my current and recent ads. Step 1 — Analyze winners: - Which ad formats performed best? (static, video, carousel, UGC) - Which hooks/headlines had the highest CTR? - Which CTAs had the highest conversion rate? - Which visual styles got the most engagement? Step 2 — Generate 5 creative briefs for new ads: Each brief should include: - Format recommendation (static/video/carousel) - Hook/headline (first 3 seconds or first line of copy) - Key message and value proposition - CTA text - Visual direction (1-2 sentences) - Why this brief should work (based on data from Step 1) Rules: - 3 of 5 briefs should iterate on proven winners (same format, different angle) - 2 of 5 briefs should test new concepts (different format or entirely new hook) - All briefs must be platform-native (not repurposed from other channels) - Include aspect ratio recommendations (9:16 for Stories/Reels, 1:1 for Feed) Here is my ad performance data (include ad name, format, primary text, headline, CTR, CVR, spend): [PASTE YOUR AD PERFORMANCE DATA HERE]

08 · Ad Copy A/B Variant Writer

Most Meta advertisers test two or three copy variants; the top performers test eight to twelve. This skill takes your best ad copy and writes eight variants that change one variable each — hook, social proof, benefit framing, CTA, length — so you know exactly what moved the needle. Run each variant to at least 2,000 impressions before judging. Cadence: per copy refresh.

Skill instruction
You are a Meta Ads copywriter specializing in direct response. I'll provide my current best-performing ad copy (primary text, headline, description, CTA). Generate 8 variants using this testing framework: 1. HOOK VARIANT (2 versions) — Change only the first line/hook. Test question vs. statement vs. statistic. 2. SOCIAL PROOF VARIANT (2 versions) — Add/change social proof element (reviews, user count, results). 3. BENEFIT FRAMING VARIANT (2 versions) — Same offer, reframed: pain-point focus vs. aspiration focus. 4. CTA VARIANT (1 version) — Change CTA text and urgency level. 5. LENGTH VARIANT (1 version) — If original is long, write a short version (or vice versa). For each variant: - Label which variable changed - Explain what you're testing and why - Keep everything else identical to the original - Follow Meta's ad copy best practices (125 chars primary text visible before "See More") Format: Variant # | Variable Tested | Primary Text | Headline | Description | CTA Here is my current best-performing ad copy: [PASTE YOUR AD COPY HERE]

09 · Budget Allocation by Funnel Stage

Most Meta accounts over-invest in prospecting and under-invest in mid-funnel. This skill classifies campaigns into TOFU, MOFU and BOFU, compares the spend split to benchmarks for your business type, and recommends dollar shifts with the expected ROAS impact. If BOFU frequency is above 8, you do not need more retargeting budget — you need more TOFU to fill the funnel. Cadence: monthly.

Skill instruction
You are a Meta Ads funnel strategist. I'll provide campaign performance data. Categorize each campaign into funnel stages: - TOFU: Cold prospecting, lookalike audiences, interest-based targeting - MOFU: Video viewers, page engagers, content interacters (warm but not yet on-site) - BOFU: Website visitors, add-to-cart, initiated checkout, customer lists Then analyze: 1. Current spend split across TOFU/MOFU/BOFU (actual %) 2. Conversion rate and CPA at each stage 3. Audience saturation at each stage (frequency + reach as % of total addressable) 4. ROAS by funnel stage Compare to benchmarks: - E-commerce: 60% TOFU / 20% MOFU / 20% BOFU - Lead gen: 50% TOFU / 30% MOFU / 20% BOFU - High-ticket B2B: 40% TOFU / 35% MOFU / 25% BOFU Output: - Current allocation vs. recommended allocation - Dollar amounts to shift between stages - Expected ROAS impact of the reallocation - Warning if any stage is saturated (frequency >3 at TOFU, >5 at MOFU, >8 at BOFU) My business type: [E-COMMERCE / LEAD GEN / B2B] Monthly Meta Ads budget: [$ AMOUNT] Here is my campaign data: [PASTE YOUR CAMPAIGN PERFORMANCE DATA HERE]

10 · Interest Targeting Expander

When existing interest audiences saturate you need new ones, and guessing is slow. This skill takes your best-performing interests and generates twenty adjacent, behavioral, affinity and contrarian targets to test — and in Cursor it also runs a web search so the suggestions use the language your customers actually use in posts. Test new interests in isolated ad sets at $20–50/day for five to seven days, no more than three interests per ad set. Cadence: when audiences saturate.

Skill instruction
You are a Meta Ads audience researcher. I'll provide my current interest targets and their performance (CTR, CPA, ROAS). First, use web search to find how people who buy [MY PRODUCT CATEGORY] describe the problem it solves — the words, communities and adjacent hobbies that show up in reviews, forums and social posts. Then generate 20 new interest targets to test, organized in 4 categories: 1. ADJACENT INTERESTS (5): Closely related to my winners, likely high-intent 2. BEHAVIORAL SIGNALS (5): Purchase behaviors, device usage, life events that correlate with my product 3. AFFINITY INTERESTS (5): Lifestyle/media interests that indicate my customer profile 4. CONTRARIAN PICKS (5): Non-obvious interests that the web research suggests correlate For each suggested interest: - Exact interest name as it appears in Meta Ads Manager - Estimated audience size range - Why this interest should work (behavioral logic, with the web evidence where relevant) - Suggested ad set structure: test alone or stack with other interests Also flag any current interests that should be retired (high spend, low ROAS). My product/service: [DESCRIBE YOUR PRODUCT] My current best-performing interests: [PASTE YOUR INTEREST TARGETS AND PERFORMANCE HERE]

Reporting skills: communicate results

Reporting skills turn raw Ads Manager data into narratives stakeholders can read without follow-up questions. The weekly digest alone saves most teams two to three hours per client per week, and the creative scorecard is what changes what the design team makes next.

11 · Weekly Meta Performance Digest

Every Monday you paste in last week's data and get the paragraph that explains what happened, why, and what you are doing about it — for a CMO with two minutes. Export campaign name, spend, impressions, CTR, CPC, conversions, CPA, ROAS and frequency, plus ad-level rows for the creative section. Cadence: weekly, Monday morning.

Skill instruction
You are a senior Meta Ads strategist writing a weekly performance report. I'll provide this week's and last week's Meta Ads data (attached, or pulled live through the MCP server). Generate a weekly digest with these sections: 1. EXECUTIVE SUMMARY (3-4 sentences) - Top-line ROAS, spend, conversions, CPA vs. last week - What drove the change (specific campaigns/ad sets) - One thing that went well, one thing to watch 2. CAMPAIGN PERFORMANCE TABLE - Campaign | Spend | ROAS | CPA | Conv | vs. Last Week (%) - Sort by spend descending - Flag any campaign with >20% CPA increase 3. CREATIVE PERFORMANCE - Top 3 performing ads (by ROAS) with why they're working - Bottom 3 ads that should be paused or refreshed - Creative fatigue warnings (any ad with CTR declining 3+ consecutive days) 4. AUDIENCE INSIGHTS - Best performing audience segment this week - Any audience showing saturation signals (frequency >3) 5. NEXT WEEK PRIORITIES (3 bullet points) - Specific, actionable items based on this week's data Tone: Professional but conversational. Write for a CMO who has 2 minutes to read this. This week's data: [PASTE THIS WEEK'S DATA] Last week's data: [PASTE LAST WEEK'S DATA]

12 · Creative Scorecard Builder

Assigns every active ad a 1–100 score from a weighted composite of CTR, conversion rate, ROAS, cost efficiency and longevity, so creative reviews run on numbers instead of opinions. Share it with the design team weekly: when UGC video scores 78 and polished brand video scores 42, direction shifts fast. Cadence: weekly.

Skill instruction
You are a Meta Ads creative performance analyst. Score every active ad on a 1-100 scale using this weighted framework: - CTR vs. account average: 25% weight - Conversion Rate vs. account average: 25% weight - ROAS vs. target: 20% weight - Cost efficiency (CPA vs. account average): 15% weight - Longevity (days active without fatigue): 15% weight Scoring bands: - 80-100: Star Performer — scale budget, create iterations - 60-79: Solid — maintain, monitor for fatigue - 40-59: Underperformer — test new variants - 0-39: Cut — pause immediately, reallocate budget Output: - Scorecard table: Ad Name | Format | Score | CTR Score | CVR Score | ROAS Score | Efficiency Score | Longevity Score | Action - Top 3 learnings from star performers (what makes them work) - Bottom 3 patterns from underperformers (what to avoid) - Creative mix recommendation: ratio of formats (static/video/carousel/UGC) Here is my ad performance data: [PASTE YOUR AD-LEVEL PERFORMANCE DATA HERE]

13 · Competitor Ad Library Analyzer

The skill that gains most from running in an editor with web search. It takes competitor data from Meta's Ad Library — or pulls it through a connector with Ad Library search — and reads format mix, refresh rate, hooks and gaps; then it runs a web search to see how audiences are reacting to those ads, which the Ad Library cannot show. Focus on competitors with many active ads; their testing tells you what works in your vertical. Cadence: monthly.

Skill instruction
You are a competitive intelligence analyst for Meta Ads. I'll provide data from Meta Ad Library for 3-5 competitors: ad copy, formats, start dates, and active status (or pull it through the MCP server's Ad Library search). Analyze: 1. CREATIVE STRATEGY - Format mix: % static vs. video vs. carousel vs. UGC - Average creative lifespan (start date to today for active ads) - Creative refresh rate (new ads per week/month) 2. MESSAGING PATTERNS - Top 3 hooks/angles each competitor uses repeatedly - Common CTAs across competitors - Unique value propositions by competitor 3. AUDIENCE REACTION ON THE WEB (use web search) - What reviews, forums and social posts say about each competitor's ads, offers and product in the last 30 days - Complaints that their ads do not address - Any launch, price change or promotion being discussed 4. TESTING VELOCITY - How many active ads does each competitor run? - How many new ads launched in the last 30 days? 5. GAPS & OPPORTUNITIES - What angles are competitors NOT covering that you could own? - What format is underrepresented across all competitors? - What complaint from the web could your next ad answer directly? Output a competitive brief with specific creative recommendations for our next sprint. My brand/product: [DESCRIBE YOUR BRAND] Competitor Ad Library data: [PASTE COMPETITOR AD DATA HERE]

14 · Audience Insights Reporter

Takes your breakdown data — age, gender, device, region, time — and surfaces the segments driving results versus the ones consuming budget. Most accounts find 70–80% of conversions come from two or three segments. Export from Breakdowns → By Demographics and By Time, at least 30 days. Cadence: monthly.

Skill instruction
You are a Meta Ads audience analyst. I'll provide audience breakdown data from my Meta Ads campaigns. Analyze across these dimensions: 1. AGE: Which age brackets convert at the lowest CPA? Which waste budget? 2. GENDER: Performance split with CPA and ROAS by gender 3. DEVICE: Mobile vs. desktop vs. tablet — conversion rate and CPA differences 4. REGION: Top/bottom performing regions or DMAs 5. TIME: Day of week and hour of day performance patterns For each dimension: - Identify the top 20% of segments driving 80% of results - Flag segments with >2x the average CPA (budget drains) - Recommend: scale, maintain, reduce, or exclude Output: - Ideal customer profile based on data (age + gender + device + region + time) - Budget waste estimate: how much is spent on underperforming segments - 3 targeting recommendations to implement this week - Day-parting schedule if performance varies significantly by time Here is my audience breakdown data: [PASTE YOUR AUDIENCE BREAKDOWN FROM ADS MANAGER HERE]

15 · ROAS by Placement Breakdown

The revenue-attribution counterpart to skill 05: true ROAS by placement accounting for assists, view-through and attribution-window sensitivity. Stories and Reels often look unprofitable on 1-day click and very profitable on 7-day click — run both windows before cutting anything. Cadence: monthly.

Skill instruction
You are a Meta Ads attribution and placement analyst. I'll provide placement-level performance data with revenue/conversion values. Analyze ROAS by placement with these considerations: 1. Direct ROAS: Revenue attributed directly to each placement 2. Assisted conversions: Placements that typically initiate but don't close (Stories/Reels often assist, Feed often closes) 3. View-through impact: Which placements drive view-through conversions? 4. Attribution window sensitivity: How does ROAS change with 1-day click vs. 7-day click vs. 7-day click + 1-day view? For each placement, provide: - Spend | Revenue | Direct ROAS | Estimated True ROAS (accounting for assists) - Role in the conversion path: Initiator, Influencer, or Closer - Recommendation: Invest more, maintain, or reduce Key analysis: - Which placement has the best true ROAS when you account for assists? - Which placement looks expensive on direct ROAS but is actually an important initiator? - Estimated revenue impact if you cut the bottom 2 placements entirely Output a placement strategy recommendation with specific budget allocations. My attribution window: [1-DAY CLICK / 7-DAY CLICK / 7-DAY CLICK + 1-DAY VIEW] Here is my placement performance data with revenue: [PASTE YOUR PLACEMENT + REVENUE DATA HERE]

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Feed the skills live data with a Meta Ads MCP server

Every skill above works on Ads Manager exports referenced with @. They work better on a live connection, because the data is never stale and the Agent can request a new breakdown without a new export. Cursor reads MCP servers from .cursor/mcp.json; a remote server needs only a url.

Add the server

Put {"mcpServers":{"ryze":{"url":"https://connector.get-ryze.ai/mcp"}}} in .cursor/mcp.json, approve the sign-in Cursor opens and authorize Meta for your ad accounts. No developer app, no app review, nothing secret in the file. About two minutes; the full walkthrough is in how to connect Cursor to Meta Ads.

Run a skill against it

In the Agent chat, type /creative-fatigue and add “use the last 14 days of ad-level insights from the ryze server”. The Agent calls the connector's raw insights tool with a daily breakdown (Cursor asks you to approve the call), applies the skill's thresholds, and writes the replace-now list to reports/.

Let it propose the change

The connector's write tools — pause, budgets, new ads through Graph writes — are approval-gated on the Ryze side and by Cursor's own tool approval. After the fatigue check, ask the Agent to pause the urgent ads and it shows you exactly what it wants to change and waits for your confirmation.

That is the ceiling of the skills-plus-MCP setup: the Agent analyzes, files the evidence and proposes, you approve. If you want the loop closed without you — creative rotated, budgets moved and audiences refreshed 24/7 and re-measured — that is what Ryze AI's Paid Ads Autopilot does on the same account, at $89/month flat. For the wider integration landscape, see the best MCP servers for Meta Ads.

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Troubleshooting: when a skill gives generic advice or numbers that do not match Ads Manager

Five failure modes account for nearly every bad output we have seen. All of them are fixable in the skill, the data or the config, not the model.

  • Slash command not found. Skills are discovered on startup — restart Cursor after adding a folder, and check the frontmatter name matches the folder name. Skills in ~/.cursor/skills/ do not show up in Cloud Agents; move them to the project.
  • Generic advice, no numbers. The @-referenced export is missing columns (frequency and daily breakdown are the usual gaps), or the MCP server is disabled for this chat. Ask the Agent which tool it called; if none, toggle the server on in the composer or re-export with all columns.
  • ROAS does not match Ads Manager. Attribution window. Put the window you report on — 7-day click, 1-day view, or both — in a rule so every skill inherits it, and say whether purchases or all conversions count.
  • Every ad flagged as fatigued. The export covers too short a window for a peak to exist. Give 14 days minimum with a daily breakdown so the skill can compare current CTR to peak CTR.
  • Output lands in the wrong place. Add the target path to the skill body (“write to reports/{today}.csv”) or to a rule; the 15 above name their outputs.

Running Google as well? The same 15-skill loop exists for that platform: Cursor skills for Google Ads. And if a skill is worth running every week, it is worth running without you — that is the case for an autopilot.

Frequently asked questions

What are Cursor Agent Skills?

Cursor Agent Skills are reusable instruction sets that teach the Agent a multi-step workflow. Each is a folder with a SKILL.md file — YAML frontmatter (name, description, optional paths) followed by Markdown instructions — stored in .cursor/skills/ or ~/.cursor/skills/, discovered on startup and invoked with /skill-name in chat or attached with @.

How do I create a Cursor skill for Meta Ads?

Type /create-skill in the Agent chat and describe it, or create .cursor/skills/<name>/SKILL.md by hand with a name and description in the frontmatter and one of the 15 instructions in this guide as the body. Restart Cursor and the skill is available as a slash command in every chat.

Can I use my Claude skills in Cursor?

Yes. Cursor reads .claude/skills/ and ~/.claude/skills/ alongside its own folders, so SKILL.md files written for Claude Code work unchanged. The 30 marketing skills on get-ryze.ai unzip straight into either folder and appear as slash commands after a restart.

Do Cursor skills work without connecting my Meta Ads account?

Yes. Every skill here works on CSV exports from Ads Manager referenced with @ in the chat, and writes its output into the repo. An MCP server makes the data live and lets the Agent request new breakdowns without exports, but it is optional. Start with exports, add the server once the skills are earning their keep.

How do I give Cursor live Meta Ads data?

Add a Meta Ads MCP server to .cursor/mcp.json. The managed Ryze AI connector needs only a url, a sign-in and Meta authorization and exposes 12 Meta Ads tools including raw insights with breakdowns, creatives and Ad Library search; self-hosted servers need a reviewed developer app. With the server enabled, skills pull data instead of asking for files.

Can a Cursor skill make changes in Meta Ads?

Only through an MCP server with write tools. Skills themselves analyze and write files; with the Ryze AI connector attached, the Agent can propose to pause fatigued ads or move budget and the change waits for your approval, on top of Cursor's own tool approval. A skill plus a read-only server never changes the account.

Which Cursor skill should I install first?

Creative Fatigue Detection. It needs one export — active ads, 14 days, daily breakdown with CTR and frequency — and leaves a replace-now list in the repo on the first run, which is the fastest CPA improvement available on Meta. Add the Weekly Meta Performance Digest second; it is the one your stakeholders will read.

What is the difference between a Cursor skill and a rule?

A rule is always-on guidance — attribution window, formats, things never to do — that shapes every answer a little. A skill is a procedure the Agent runs on demand with a defined method and output. Use a rule for “7-day click attribution, never mutate without approval” and skills for each audit.

Do Cursor skills work in Cloud Agents?

Project-level skills in .cursor/skills/ do, because they travel with the repo. User-level skills in ~/.cursor/skills/ are not copied to Cloud Agents, remote SSH windows or self-hosted workers. Put team skills in the project folder and commit them.

Can Cursor run these skills on a schedule?

Not from the desktop app by itself. A Cloud Agent can run a project skill against a remote MCP server, and the Agent can write a Python script against the Meta Business SDK that runs the same logic on a cron. For changes that should happen without you, an autopilot such as Ryze AI executes on its own schedule.

Which skills use web search?

Two. The Competitor Ad Library Analyzer adds how audiences are reacting to each competitor's ads and offers, and the Interest Targeting Expander uses the web to find the language and adjacent communities your buyers actually use. Both add context the Ad Library and Ads Manager cannot show, and both file their findings in the repo.

Cursor vs Claude for Meta Ads skills — which is better?

The skill files are interchangeable, so the analysis quality depends more on the skill than the model. Claude is the better chat analyst; Cursor's advantage is that outputs land as files and code in the same repo, and skills run as slash commands. Many teams run the same skills in both.

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Last updated: Sep 2, 2026
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