Install
$ agentstack add skill-hayesti54-eng-ai-media-buying-skills-monthly-performance-reporter ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
LSA Monthly Performance Reporter
Platform: Google LSA Category: reporting Tier: pro
Purpose
Produce a comprehensive monthly performance report for a Google LSA account that goes beyond weekly operational monitoring to deliver trend analysis, cost efficiency assessment, dispute reconciliation, ranking health summary, and strategic recommendations for the following month. The monthly report is the strategic document — it answers not just "what happened" but "why it happened," "what changed month over month," and "what do we change next month to improve outcomes."
When to Use
- At the end of every calendar month as a standard client-facing deliverable
- When presenting a monthly business review (MBR) for agency-managed LSA accounts
- When a month had significant events (budget change, staffing change, profile update) that require documented analysis
- When comparing performance across months to identify seasonality patterns
- When a client is evaluating whether to continue, expand, or reduce LSA investment
Inputs Required
- Full LSA dashboard data for the month: all leads, spend, lead types, responsiveness score
- CRM data: all LSA-sourced booked jobs for the month, revenue generated, job type breakdown
- Dispute log for the month: disputes filed, disputes resolved, credits received
- Budget cap history for the month (any cap changes made)
- Review activity: new Google reviews received in the month, current rating
- Profile changes made during the month
- Prior month data for MoM comparison
- Year-ago data for same month (if available) for seasonality context
What This Skill Does
Builds a complete monthly LSA performance narrative from raw data. Calculates and contextualizes every core performance metric, identifies the primary performance drivers (positive and negative) for the month, reconciles dispute activity and credit recovery, summarizes ranking health changes, and produces a strategic recommendation set for the following month. Designed to be the primary communication artifact between the account manager and the client at the monthly review — detailed enough to be credible, concise enough to be consumed in a 30-minute meeting.
Analysis Workflow
- Compile all lead data for the month: total by type, total by week, weekly trend within the month.
- Calculate all core metrics: total spend, CPL, call answer rate, booked lead count, booked lead rate, cost-per-booked-lead, total LSA-sourced revenue, LSA ROAS.
- Calculate MoM changes for every core metric — identify which metrics improved, which declined, and the magnitude of each change.
- Produce a weekly performance chart description showing lead volume and spend distribution across the 4–5 weeks of the month.
- Assess responsiveness health for the month: average score, any score dips, and their delivery impact.
- Reconcile dispute activity: total disputes filed in the month, resolution outcomes (approved/denied), total credit recovered, estimated credits still pending.
- Review ranking position observations: any notable rank changes during the month and their attributed causes.
- Assess budget efficiency: average weekly utilization, any weeks where throttling occurred, any budget cap change impact.
- Review new Google reviews received: count, rating distribution, and net rating change for the month.
- Identify the top 3 performance drivers (positive and negative) for the month with supporting evidence.
- Benchmark the month against the prior 3-month average for trend context.
- Write strategic recommendations for the following month: 3–5 specific changes with supporting rationale.
Output Requirements
- Executive summary: month performance narrative in 5–7 sentences — headline metric, key win, key concern, and primary recommendation
- Core metrics dashboard: full month metrics vs. prior month with MoM % change for each
- Weekly trend breakdown: lead volume and spend by week within the month
- Responsiveness health summary: monthly average, any score events, delivery impact
- Dispute reconciliation: total filed, resolved, denied, credited — credit recovery amount
- Review activity summary: new reviews, rating change, cumulative review count
- Performance driver analysis: top 3 positive and negative factors with evidence
- Trailing 3-month trend table: core metrics for current month + 2 prior months
- Next-month strategic recommendations: 3–5 actions with rationale and expected impact
Platform-Specific Best Practices
- Monthly reports must include dispute credit reconciliation — recovering even one denied dispute is real money and clients notice when it is tracked.
- LSA ROAS reporting requires reliable CRM revenue attribution — flag any month where attribution confidence is low rather than reporting a misleading number.
- Seasonal patterns are powerful context for LSA performance in home services — a "down month" in February is normal for most trades; frame MoM declines appropriately.
- The next-month recommendation section is the highest-value part of the report for retention — it demonstrates forward-looking strategic thinking, not just data compilation.
- Booked lead rate should be the headline conversion metric in every monthly report — not raw lead volume, not just spend.
- Month-over-month review growth is a strategic KPI, not just a vanity metric — review velocity directly affects rank trajectory.
Guardrails
- Do not report LSA ROAS without confidence-flagging attribution quality — incomplete CRM tagging produces false ROAS numbers that will erode client trust when reality diverges.
- Do not present a month with external suppression factors (holidays, weather events) as equivalent to a normal month without contextualizing those factors.
- Strategic recommendations must be specific and actionable — "improve lead quality" is not a recommendation; "remove the drain cleaning job type based on 12% booking rate" is.
- Do not omit underperformance — a credible monthly report acknowledges what went wrong and why; clients who receive only positive framing disengage from the data.
Example Requests
- "Build the March monthly report for our HVAC client. Here's the dashboard export and CRM numbers. I need it ready for the MBR call on April 3rd."
- "This was our best month ever on LSA — 67 leads, 41 booked, $28K in revenue. Build the full monthly report and set the benchmark for April targets."
- "March was down 22% from February — I need the monthly report to explain what happened and frame the next-month recommendations for the client."
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: hayesti54-eng
- Source: hayesti54-eng/ai-media-buying-skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.