kai-weekly-audit

name

kai-weekly-audit

description

Weekly marketing audit and operating review. Pulls the last 7 days of source-backed marketing, analytics, content, paid media, lead, watcher, and audit data; compares it to the prior 7 days; flags urgent issues; and produces a weekly scorecard plus action list. Use when "weekly audit", "weekly marketing review", "weekly check-in", "weekly scorecard", "what changed this week", "Friday marketing review", or any request for a recurring 7-day marketing audit.

kai-weekly-audit - Weekly 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 fast weekly operating audit. This skill is the cadence layer above /kai-audit, /kai-seo-audit, /kai-cro, /kai-daily-ad-review, /content-report, and watcher output.

Non-Negotiable: Data Provenance

Before writing findings, load harness/references/audit-data-provenance.md.

Declare the data mode:

• sales_external for prospect/public-only weekly reviews.
• 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Do not publish review counts, rankings, traffic, conversions, calls, ad metrics, Core Web Vitals, backlinks, or revenue without source, retrieval date, and artifact path.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/weekly/<YYYY-MM-DD> --audit-dir

Phase 0: Load Context

1. Read MARKETING.md.
2. Identify the brand, URL, active channels, conversion events, offer, business type, and connected sources.
3. Ask only for missing items that block a sourced review: URL, data mode, available connected sources, or target conversion event.

Phase 1: Collect Weekly Data

Create the weekly audit folder:

workspace/audits/weekly/<YYYY-MM-DD>/

Run the shared collector for the target site:

python -m scripts.audit.collect --url "<url>" --mode <mode> --workflow kai-weekly-audit --out workspace/audits/weekly/<YYYY-MM-DD> --pagespeed

Use connected collectors only when access is confirmed:

python -m scripts.audit.collect --url "<url>" --mode onboarding_connected --workflow kai-weekly-audit --out workspace/audits/weekly/<YYYY-MM-DD> --pagespeed --places --gsc --ga4 --calls --date-from "<YYYY-MM-DD>" --date-to "<YYYY-MM-DD>"

Add paid and content 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

If a command cannot run because credentials are missing, record the exact missing source in _data-gaps.md.

Phase 2: Compare Periods

Use last 7 complete days as the primary period and the prior 7 complete days as comparison.

Review these areas when data exists:

Area	Weekly Question
Revenue or pipeline	Did qualified demand, revenue, or pipeline move materially?
Website and CRO	Did traffic quality, speed, conversion, or form/call capture degrade?
SEO and AEO	Did indexed visibility, crawl health, search queries, or AI-search readiness change?
Paid media	Did spend, CPL, ROAS, CPA, CTR, CPC, or frequency drift outside guardrails?
Content	Which new or aging pieces need action?
Social and community	Did reach, engagement, replies, or audience quality change?
Lifecycle and CRM	Did follow-up, reply rate, lead aging, or handoff quality change?
Calls and reviews	Did missed calls, after-hours demand, reviews, or reputation signals need action?
Watchers	Which alerts repeated or escalated?

Only score metrics present in audit-data.json, connected exports, or raw pull artifacts.

Phase 3: Scorecard

Produce a short weekly scorecard:

Score	Meaning
Green	On track; no immediate intervention.
Yellow	Needs attention this week.
Red	Requires immediate owner decision or fix.
Gray	Not scored because data is missing.

Each scored item must include:

claim: ""
source_tier: connected | public_observed | user_provided | inferred | missing_data
source_name: ""
source_url: ""
retrieved_at: ""
evidence_artifact: ""
score_eligible: true | false

Phase 4: Weekly Actions

Create three action groups:

• Do this week - P0/P1 issues with clear owner and due date.
• Watch next week - items with trend risk but insufficient evidence for action.
• Needs data - sources or exports required before the next review.

Map recommended fixes to Kai skills:

Finding	Skill
Site or funnel issue	/kai-cro or /kai-landing-page
Search issue	/kai-seo-audit or /kai-surround-sound
Paid issue	/kai-daily-ad-review or /kai-ad-campaign
Content issue	/content-report, /content-retro, or /kai-content-calendar
Lifecycle issue	/kai-email-system or /kai-retention
Strategic drift	/kai-growth-plan
Client-ready deck needed	/kai-html-presentation

Phase 5: Output

Write:

workspace/audits/weekly/<YYYY-MM-DD>/
+-- _data-sources.md
+-- _data-gaps.md
+-- audit-data.json
+-- kai-data.json
+-- _weekly-scorecard.md
+-- _weekly-findings.md
+-- _weekly-actions.md
+-- _skill-routing.md
+-- html-presentation/
    +-- index.html

Use /kai-html-presentation to turn the weekly report into html-presentation/index.html when the user asks for a client-ready delivery artifact.