Works with the AI tools you already use
AI Automation QA & UAT Pack
This skill transforms your AI agent into a Senior QA Lead specializing in AI automations and agentic workflows.
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See it in action
You say
I've built an n8n workflow that pulls new leads from a Google Sheet, summarizes their LinkedIn profiles using OpenAI, and pokes them in Slack. It needs a full QA and UAT pack before handoff.
Your agent does
MODE: BUILD
Gate 1: Acceptance Criteria AC-01: Given 1 new row in Sheet, When workflow triggers, Then 1 Slack message is sent and row marked 'PROCESSED'. AC-02: Given a duplicate UUID, When re-run, Then no duplicate Slack message is sent (Idempotency).
Gate 3: Non-Determinism Plan
- Golden set: 10 diverse profiles.
- Rubric: Summary must include 'Current Role' and 'Recent Projects'. Must NOT hallucinate non-existent degrees.
- Stability: Run 5x; summaries must maintain 90% semantic similarity.
What you get
About this skill
What it does
This skill transforms your AI agent into a Senior QA Lead specializing in AI automations and agentic workflows. It bridges the gap between traditional software testing and the non-deterministic reality of LLMs. Whether you are building a complex n8n/Make workflow or a custom agentic pipeline, this skill generates the rigorous testing frameworks required to move from 'it works on my machine' to production-ready reliability.
Why use this skill
Generic AI prompts often miss the subtle failure modes of automation, such as silent API drops, prompt drift, or idempotency breaks during retries. This skill is better than manual prompting because it follows a structured 'Gate' methodology—covering everything from Given/When/Then acceptance criteria to adversarial non-determinism test plans that verify LLM stability. It ensures you never ship a workflow that could cause 'silent' business damage.
Key Deliverables
- Acceptance Criteria: Testable Given/When/Then statements with observable pass conditions.
- UAT Scripts: Step-by-step human-readable instructions for client sign-off.
- Non-Determinism Plan: Specialized rubrics for evaluating flaky LLM outputs and prompt injections.
- Failure-Mode Matrix: A comprehensive map of how the system handles rate limits, timeouts, and partial runs.
- Audit Reports: Scored findings for existing workflows to identify high-risk gaps before they fail in the wild.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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