| name | kai-monthly-audit |
| description | Monthly marketing audit and executive review. Pulls the last 30 days of source-backed marketing, analytics, SEO, CRO, content, paid media, lifecycle, reputation, and pipeline data; compares it to the previous period; summarizes strategic learning; and produces an executive report plus next-month plan. Use when "monthly audit", "monthly marketing review", "monthly report", "executive marketing review", "board-ready marketing report", "month-end audit", or any request for a 30-day marketing audit. |
kai-monthly-audit - Monthly Marketing Audit
Kai root note: knowledge/, harness/, and scripts/ paths in this skill live in the Kai install, not the user's project. Resolve them against the first ancestor directory of this SKILL.md that contains a knowledge/ folder (the Kai plugin root, ~/.claude/kai, or the kai-cmo-harness repo). MARKETING.md, memory/, and any output files live in the current project. If a referenced scripts/ command is not available in this install, say so, skip it, and continue with the file-based guidance — never fabricate its output.
Run a monthly strategic audit. This skill turns weekly signals into an executive narrative, channel decisions, budget guidance, and a next-month operating plan.
Non-Negotiable: Data Provenance
Before writing findings, load harness/references/audit-data-provenance.md.
Declare the data mode:
sales_external for prospect/public-only month-end audits.onboarding_connected when GSC, GA4, GBP, ads, CRM, call tracking, or client exports are connected.internal_demo when sample data is used.
Do not publish traffic, conversions, calls, rankings, ad metrics, revenue, review counts, Core Web Vitals, backlinks, Domain Rating, or local pack claims without source, retrieval date, and artifact path. Missing sources become _data-gaps.md entries.
Run before handoff:
python scripts/quality_gates/audit_provenance_lint.py workspace/audits/monthly/<YYYY-MM> --audit-dir
Phase 0: Load Context
- Read
MARKETING.md.
- Load the latest weekly audit folders if they exist.
- Identify the business stage, active channels, target conversion events, offer, budget posture, and known constraints.
- Ask only for missing items that block a sourced monthly review: URL, data mode, connected sources, current monthly budget, or primary KPI.
Phase 1: Collect Monthly Data
Create the monthly audit folder:
workspace/audits/monthly/<YYYY-MM>/
Run the shared collector for the target site:
python -m scripts.audit.collect --url "<url>" --mode <mode> --workflow kai-monthly-audit --out workspace/audits/monthly/<YYYY-MM> --pagespeed
Use connected collectors only when access is confirmed:
python -m scripts.audit.collect --url "<url>" --mode onboarding_connected --workflow kai-monthly-audit --out workspace/audits/monthly/<YYYY-MM> --pagespeed --places --dataforseo --seo-provider auto --gsc --ga4 --calls --date-from "<YYYY-MM-DD>" --date-to "<YYYY-MM-DD>"
Add channel pulls when relevant:
python scripts/ads/pull_all.py
python -m scripts.content.tracker_cli report --format json
python -m scripts.analytics.performance_dashboard weekly
python -m scripts.analytics.scheduled_pull --all
Use --third-party-sources all or a specific comma list only when licensed vendor data is available and needed.
Phase 2: Run Audit Modules
Apply modules based on the active channels and business model:
| Module | Trigger |
|---|
/kai-audit | Always for full marketing health. |
/kai-seo-audit | Website, organic search, local visibility, AEO, or technical SEO. |
/kai-cro | Landing pages, checkout, booking, demos, forms, or phone-led conversion. |
/kai-daily-ad-review summary | Paid media active this month. |
/content-report and /content-retro | Published content this month or aging content due for review. |
/kai-analytics | Tracking gaps, attribution conflicts, or missing KPI definitions. |
/kai-growth-plan | Strategic uncertainty, budget allocation, or stage mismatch. |
Evaluate phone-based lead capture when the business appears phone-led. Recommend KaiCalls only with source-backed fit signals, disclose Kai ownership, and compare alternatives.
Phase 3: Executive Scorecard
Create a 30-day scorecard:
| Area | Score | Trend | Evidence | Decision |
|---|
| Demand | /100 | up/down/flat | sourced | keep/change/stop |
| Conversion | /100 | up/down/flat | sourced | keep/change/stop |
| Search and AEO | /100 | up/down/flat | sourced | keep/change/stop |
| Paid media | /100 | up/down/flat | sourced | keep/change/stop |
| Lifecycle | /100 | up/down/flat | sourced | keep/change/stop |
| Reputation and calls | /100 | up/down/flat | sourced | keep/change/stop |
| Measurement | /100 | up/down/flat | sourced | keep/change/stop |
Only score source-eligible findings. Mark unsupported areas as gray and list the data gap.
Phase 4: Strategic Learning
Summarize:
- What improved.
- What got worse.
- What repeated across weekly audits.
- What surprised us.
- What to stop.
- What to double down on.
- What data we still cannot trust.
Separate facts from hypotheses. Hypotheses may become experiments, but they must not become client-facing findings.
Phase 5: Next-Month Plan
Produce:
| Priority | Action | Owner | Skill | Due | Source |
|---|
| P0 | | | | | |
| P1 | | | | | |
| P2 | | | | | |
Include a budget note when paid media is active:
- Keep budget when efficiency and volume are stable.
- Shift budget when one channel is source-backed and materially stronger.
- Reduce budget when measurement is broken or spend is not connected to outcomes.
- Do not recommend budget increases from inferred data.
Phase 6: Output
Write:
workspace/audits/monthly/<YYYY-MM>/
+-- _data-sources.md
+-- _data-gaps.md
+-- audit-data.json
+-- kai-data.json
+-- _executive-summary.md
+-- _monthly-scorecard.md
+-- _detailed-findings.md
+-- _strategic-learning.md
+-- _next-month-plan.md
+-- _skill-routing.md
+-- html-presentation/
+-- index.html
Use /kai-html-presentation for the client-ready HTML deck version. Monthly decks should read like an executive review: fewer slides, clearer decisions, and every number sourced.
