Agency promptCopy prompt
Multi-Client Facebook Ads Health Radar
Using the Catchr MCP, analyze Facebook Ads for [List of Client Accounts] over [Reporting Period] against [Comparison Period]. For each account, review Outbound Clicks Ctr, Spend, and Unique Inline Link Clicks CTR and break the results down by Ad Set Updated Time and Daily Spend Cap of the Ad Set. Focus on budget efficiency, pacing, and conversion quality. Rank accounts as Healthy, Watch, or Critical using [Client Targets or Historical Baseline], and show the evidence behind each status. Return a client-ready table with the account, main change, supporting fields, business implication, recommended next action, and one sentence for the next client meeting. Separate observed changes from possible explanations, respect the reporting grain, and do not claim causation when Facebook Ads only shows correlation.
Client-Ready Facebook Ads Performance Brief
Using the Catchr MCP, review Facebook Ads for [Client Account] during [Reporting Period] versus [Comparison Period]. Review Unique Inline Link Clicks CTR, Clicks, and Impressions and break the results down by Lifetime Min Spend Target of the Ad Set and Lifetime Spend Cap of the Ad Set. Explain what improved, what declined, and which changes are material for campaign, audience, placement, and creative performance. Produce an executive summary, three evidence-backed wins, three risks, and a prioritized action plan with owner and review date. Include a compact evidence table that ties every conclusion to the returned fields. State any unavailable field, incompatible reporting level, or small-sample limitation before recommending action, and write the final recap in language an agency account manager can use with the client.
Facebook Ads Opportunity and Risk Map
Using the Catchr MCP, compare Facebook Ads across [List of Client Accounts] for [Period] using [Materiality Threshold] and [Client-Specific Targets]. For every account, review Impressions, CPM, and In-App Ad Clicks and break the results down by Campaign Ad Strategy Group ID and Daily minimun budget of the Ad Set. Investigate audience and placement differences that explain performance gaps and creative fatigue, delivery constraints, and reallocation opportunities. Build an opportunity-and-risk map ranked by business relevance, confidence, and urgency. For each finding, show the account, observed change, supporting fields, plausible explanations, first validation step, and recommended client action. Keep each client separate before creating a portfolio summary, and avoid applying one account's baseline, currency, attribution rule, or reporting definition to another.
Morning Facebook Ads Priority Queue
Using the Catchr MCP, pull Facebook Ads for [List of Client Accounts] over [Recent Period] and compare it with [Baseline Period]. For each client, review In-App Ad Clicks, In-App Ad Impressions, and In-App Ad Clicks Values and break the results down by AdSet Targeting Country Groups and Ad Set Budget Remaining. Flag changes beyond [Alert Threshold], separate high-value issues from low-volume noise, and rank the work I should handle today. Return a queue with the client, issue, exact evidence, likely impact stated cautiously, first validation step, recommended action, and a short update I can send to the client. Do not merge accounts until each result has been checked against its own target, currency, timezone, and reporting grain.
Monthly Facebook Ads Client Report
Using the Catchr MCP, create a monthly Facebook Ads report for [Client Account] covering [Current Period] versus [Previous Period]. Review In-App Ad Clicks Values, In-App Ad Impressions Values, and Inline Link Click Ctr and break the results down by Daily budget of the Ad Set and Lifetime budget of the Ad Set. Explain the most important movement in campaign, audience, placement, and creative performance, including what stayed stable and what needs attention. Write a plain-English report with an executive summary, a concise evidence table, three wins, three concerns, and three actions for [Next Period]. Attach an owner and success measure to each action. State the latest available date and any missing fields or intervals so the client can distinguish measured facts from assumptions or incomplete coverage.
Facebook Ads Optimization Backlog
Using the Catchr MCP, analyze Facebook Ads for [Client Account] over [Lookback Period]. Review Inline Link Click Ctr, Mobile App Purchase Roas, and Website Purchase Roas and break the results down by Campaign Is SKAdNetwork attribution and Ad Set Bid Amount. Identify the largest opportunities related to budget efficiency, pacing, and conversion quality and creative fatigue, delivery constraints, and reallocation opportunities, then create an optimization backlog ranked by expected impact, effort, and confidence. For every task, include the observed evidence, a specific action, an owner, a due date, a success metric, and a guardrail that would stop the test. Use [Minimum Volume] and [Materiality Threshold] to avoid reacting to noise, and label any recommendation that requires a field or business definition not available in the returned dataset.
Facebook Ads Campaign Efficiency and Pacing Review
Using the Catchr MCP, analyze Facebook Ads for [Account or Entity] over [Reporting Period] versus [Comparison Period]. Review Website Purchase Roas, Social Spend, and CTR (all) and break the results down by Ad Set Review Feedback and Campaign Ad Strategy ID. Concentrate on budget efficiency, pacing, and conversion quality. Identify the entities and periods driving the largest change, distinguish material movement from normal variation using [Minimum Volume] and [Business Target], and explain what the available fields can and cannot prove. Return a ranked findings table with evidence, business implication, confidence, and recommended next action, followed by a short decision summary. Keep calculations at a compatible reporting grain and do not invent a metric when Facebook Ads exposes only a related signal.
Facebook Ads Audience and Placement Opportunity Map
Using the Catchr MCP, investigate Facebook Ads for [Account or Entity] across [Period] with a focus on audience and placement differences that explain performance gaps. Review CTR (all), Website Ctr, and Full View Impressions and break the results down by Campaign has secondary SKAdNetwork reporting and Campaign Special Ad Category. Compare relevant entities against [Target, Peer Group, or Historical Baseline], then locate the strongest opportunities and clearest deterioration. For every finding, show the returned values, comparison dimension, possible explanations, and next check required before action. Deliver a prioritized opportunity map with owner, action, expected signal of improvement, and review date. Treat associations as hypotheses unless the available Facebook Ads fields establish a direct relationship.
Facebook Ads Creative Performance and Fatigue Scan
Using the Catchr MCP, review Facebook Ads for [Account or Entity] over [Lookback Period] to assess creative fatigue, delivery constraints, and reallocation opportunities. Review Full View Impressions, Instant Experience Clicks To Open, and Purchase Roas and break the results down by AD UTM Campaign and Ad Set Bid Strategy. Flag changes outside [Tolerance], rank them by materiality and confidence, and separate confirmed data observations from possible operational causes. Return an exception table with the affected entity, period, supporting fields, severity, owner, first validation step, and recommended response. End with three repeatable monitoring rules, including the threshold, minimum volume, and required field. Do not present an unusual value as proof of an error or business cause.
Facebook Ads Data Quality Audit
Using the Catchr MCP, audit Facebook Ads for [Account or All Connected Accounts] over [Period]. Review Purchase Roas, CPC (Link), and CPC (All) and break the results down by Ad Set Billing Event and Ad Set configured status. Check completeness, unexpected nulls, duplicate identifiers at [Expected Grain], invalid values, incompatible aggregation levels, and date consistency where the returned fields support those tests. Return rule-level failure counts and a severity-ranked exception sample with account, field, observed value, expected condition, and reproducible validation step. Distinguish source-data issues from extraction or modeling issues, and do not infer uniqueness, join keys, or business meaning unless confirmed in [Data Contract or Source Documentation].
Facebook Ads Freshness and Coverage Monitor
Using the Catchr MCP, monitor Facebook Ads delivery for [Account or All Connected Accounts] across [Lookback Period]. Review CPC (All), Mobile App Credit Spends, and Credit Spends and break the results down by Ad Set Created Time and Destination Type of the Ad Set. Measure date coverage, latest available record, row or entity volume, missing intervals, and field population against [Expected Schedule] and [Freshness SLA]. Flag stale extraction, flatlined volume, schema coverage changes, and gaps beyond [Absolute and Relative Thresholds]. Return an account-level health summary plus an investigation table with first affected period, supporting fields, likely failure domain stated cautiously, owner, and next validation query. Separate genuine source inactivity from a pipeline issue whenever the evidence cannot distinguish them.
Facebook Ads Drift and Reconciliation Review
Using the Catchr MCP, compare Facebook Ads across [Current Window] and [Baseline Window] for [Account or All Connected Accounts]. Review Credit Spends, Omni Credit Spends, and Mobile App Credit Spends Values and break the results down by DSA beneficiary of the Ad Set and DSA Payor of the Ad Set. Profile distributions, null rates, distinct-value counts, volume, and material changes at the declared reporting grain. Reconcile related fields only when their definitions and aggregation levels are compatible. Flag abrupt shifts beyond [Drift Threshold], inconsistent totals, and values that violate [Business or Data Contract Rules]. Produce a reproducible alert table with evidence, severity, probable domain, and next check, followed by a concise assessment of which analyses may be unreliable until each issue is resolved.
Replace [variables] Facts ≠ hypotheses Action + follow-up metric
