Workflow Testing

Use when validating automation builds before launch or after significant changes.

Published by @gtmagents·from gtmagents/gtm-agents·0 agent reads / 30d·0 saves·Updated June 14, 2026

Workflow Testing & QA Skill

When to Use

Any new automation or major revision prior to go-live.
Regression testing after data, asset, or logic changes.
Investigating deliverability, conversion, or routing anomalies.

Framework

Unit Tests – confirm each branch, wait step, and action path with seed contacts.
Integration Tests – verify webhook/API calls, CRM updates, enrichment, scoring.
Content QA – links, tracking, personalization tokens, accessibility, localization.
Compliance – consent, suppression, GDPR/CASL/CCPA rules, regional requirements.
Performance – throttle checks, concurrency, error handling, failover.

Checklist

Seed list matrix (personas, stages, regions, consent flags).
Device/browser testing for email/SMS/push rendering.
Logging + alerting validation.
Rollback and kill switches documented.

Templates

QA evidence log (screenshot, recipient, status, owner).
Incident runbook for automation failures.
Release checklist referencing stakeholders.

Tips

Automate regression tests via APIs or synthetic users.
Store test data separately and purge regularly to avoid reporting noise.
Use feature flags to stage rollouts before full scale.

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Connect via MCP.

Add the public bench to any AI tool. Your agents read every artifact you see — no signup needed.

1Pick your tool

# Add the public bench as an MCP server
claude mcp add --transport http sharebench-public https://mcp-public.sharebench.ai

# Settings → MCP → Add new MCP server
{
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}

# Custom GPT or Developer Mode
# Add a remote MCP connector with this URL:
https://mcp-public.sharebench.ai

# Append to ~/.codex/config.toml
[mcp_servers.sharebench_public]
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2Ask your agent for an artifact

Once connected, just ask in plain language — your agent searches the bench and pulls in what it needs.“Pull the brand voice from sharebench and rewrite this draft.”