Campaign Launch QA

Validate campaign readiness across 10 execution layers — brief, audience, creative, media, landing page, CRM/journey, tracking, approvals, reporting, and operations — and issue a scored go/no-go recommendation before any campaign goes live.

How This Skill Orchestrates

This skill is the governance gate of the OS. It runs after all other skills have done their work:

1. Script execution (scripts/qa_scorer.py): Scores readiness across 10 layers with 50+ checklist items, detects blockers, calculates weighted readiness score, issues go/no-go
2. Reference lookup (references/tech_stack_enablers.md): When the user names their tech stack (SFMC, AJO, AEM, HubSpot), load the platform-specific enablers checklist and validate against it
3. Upstream context (Claude): Pull campaign details from earlier skills — scope from scope-audit, team from fte-capacity-sizing, budget validation from margin-simulation
4. Visual output (Visualizer): Render the QA dashboard as a readiness scorecard with layer-by-layer results

No ML models are used. This is a governance / anomaly detection problem solved with rule-based risk scoring — a weighted checklist with critical-item blocker logic. The checklist itself is the model.

70/30 split on QA: ~62% of QA items can be automated by AI agents (UTM validation, tag firing, link checks, spec verification, rendering tests), while ~38% require human judgment (creative quality, brand compliance, strategic alignment, client approvals).

Quick Reference