Experiment Verification Monitoring
Use this skill to prevent misconfigured or unhealthy experiments from producing bad evidence. It focuses on verification before launch, canaries, A/A tests, leakage and interference checks, active monitoring, and quality roadmap metrics.
Source Traceability
Primary source: Next-Level A/B Testing by Leemay Nassery. Guidance is transformed and paraphrased from Chapter 5 on experiment effectiveness, prelaunch verification, QA tooling, canaries, A/A tests, spillover effects, and active monitoring.
Related skills:
ab-test-design-brieffor planning an experiment before verification.experimentation-throughput-strategyfor monitoring overlap conflicts.trustworthy-experiment-insightsfor statistical credibility after results.
Reference Routing
| Need | Read |
|---|---|
| Verification concepts | references/core/knowledge.md |
| QA, canary, A/A, and monitoring rules | references/core/rules.md |
| Failure scenarios and examples | references/core/examples.md |
| Step-by-step quality roadmap | workflows/create-experiment-quality-roadmap.md |
Workflow
- Define the experiment quality risks the platform must catch.
- Add prelaunch verification for assignment, targeting, exposure, treatment, metrics, and user experience.
- Add early launch canaries and active monitoring for misconfiguration.
- Run periodic A/A tests to validate infrastructure health.
- Track quality metrics and update the experimentation playbook.
- Define owners and escalation paths for active experiment issues.
Output Format
# Experiment Verification And Monitoring Plan
## Quality Risks
[What errors or trust failures this plan should prevent.]
## Prelaunch Checks
| Check | Method | Owner | Pass/Fail Criteria |
|-------|--------|-------|--------------------|
## Active Monitoring
- Canary:
- Dashboards:
- Alerts:
- Leakage/interference checks:
## Platform Health
- A/A test cadence:
- Quality metrics:
- Review process:
## Escalation Rules
- Pause if:
- Restart if:
- Investigate if:
Quality Bar
- Do not rely on manual QA alone when the platform has recurring setup errors.
- Do not launch experiments without verifying assignment, exposure, and metrics.
- Do not treat A/A tests as one-time setup checks; use them as periodic health checks when platform trust matters.
- Do not monitor only final results; active tests need early health signals.
Source: hashgraph-online/awesome-codex-plugins → plugins/LVTD-LLC/skills/skills/experiment-verification-monitoring/SKILL.md