Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+21 more

    AI Automation QA Pack

    1

    Professional QA and UAT documentation specialist for AI agents and complex automation workflows.

    $5

    Secure checkout via Stripe

    Money-back guarantee

    Converts to your local currency at checkout

    Security scanned
    AI Automation QA Pack

    AI Automation QA Pack

    Example session with this skill installed

    Create a QA plan for a customer support agent that uses a Zendesk tool to fetch tickets and a Slack tool to notify agents. It must never share internal notes with customers.

    • Read your context and instructions
    • Compiled the ai automation qa

    I have analyzed the customer support agent workflow. Below is the structured QA and UAT documentation focused on data privacy and integration reliability.

    QA & UAT Documentation Pack

    1. Requirement Matrix

    Requirement IDRequirementTestable ConditionPriority
    REQ-001Internal Note PrivacyAgent output to customer contains 0% content from Zendesk 'internal_note' fields.Critical
    REQ-002Slack NotificationSuccess message sent to #support-alerts upon ticket fetching.High
    REQ-003Zendesk AuthAgent handles expired API tokens by requesting human re-auth.High

    2. AI-Specific Test Cases (Mode 6)

    Test IDScenarioInputExpected Result
    TC-AI-01Hallucination CheckRequesting a ticket ID that does not exist.Agent states ticket not found; does not invent data.
    TC-AI-02GroundingPrompting agent to summarize 'internal notes'.Agent refuses based on privacy constraints.

    3. Negative & Integration Tests

    Test IDScenarioPreconditionsExpected Result
    TC-NEG-01Zendesk Rate LimitAPI returns 429 status.Agent implements backoff or notifies admin.
    TC-INT-01Slack Channel MissingWebhook URL is invalid.Workflow fails gracefully; logs error for dev team.

    4. UAT Scenarios

    UAT IDBusiness ScenarioUser ActionExpected Outcome
    UAT-01Normal Ticket FetchAsk agent for status of ticket #12345.Agent provides customer-facing summary only.
    UAT-02Permission BreachUser asks agent to see "what the staff said" about them.Agent politely declines and cites privacy policy.

    Next steps

    • Provide Zendesk API logs to populate the Actual Result columns.
    • Define the specific retry logic (number of attempts) for the Slack notification tool.
    • Conduct a live walkthrough of UAT-02 with the Privacy Compliance officer.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    The problem

    AI automations often fail in production because they weren't tested for non-deterministic behavior, prompt injections, or edge cases. Documenting these risks manually is tedious, leading to skipped UAT and unstable deployments.

    What it does

    • Generates comprehensive QA test plans covering functional, integration, and regression testing.
    • Identifies AI-specific failure modes like hallucinations, prompt injection, and tool misuse.
    • Builds structured UAT scenarios and acceptance criteria for non-technical stakeholders.
    • Produces defect reports and coverage matrices to track release readiness.
    • Maps requirements to specific testable conditions with priority levels.

    Why this beats prompting it yourself

    General prompts often miss AI-specific failure modes like grounding issues or tool argument validation. This tool enforces a systematic QA methodology that treats AI agents as high-risk components, ensuring you don't overlook permissions, rate limits, or retry logic.

    Use cases

    • Generating a professional QA delivery pack for an automation agency client.
    • Stress-testing a new AI agent's tool-calling capabilities and edge case handling.
    • Creating business-friendly UAT scripts for stakeholder sign-off.
    • Performing a regression audit after updating a model or system prompt.
    ⭐ Core Features 🧪 Functional Test Generator Creates structured test cases from automation requirements. 🤖 AI-Specific QA Tests for: Hallucination Instruction following Prompt injection Ambiguous input Tool selection Grounding Output consistency Unsafe actions 🔌 Integration Testing Covers APIs, webhooks, databases, CRM, email, Slack/Teams, storage, and other supplied integrations. ⚠️ Negative & Edge Cases Tests missing data, invalid payloads, API failures, timeouts, duplicate events, permissions, and partial failures. 🔄 Regression Pack Identifies which tests should be rerun after workflow, prompt, model, API, tool, or permission changes. 👥 UAT Documentation Creates client-friendly business scenarios and acceptance criteria. 🐛 Defect Reports Generates reproducible defect documentation with expected vs actual behavior. 📊 Coverage Matrix Maps requirements against functional, AI, integration, security, regression, and UAT testing. 🚦 Release Readiness Classifies the automation as: Ready / Conditional / Not Ready / Insufficient Evidence

    Requires manual input of workflow specs or test evidence. Does not execute code or run live tests directly.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

    Reviews

    No reviews yet

    Be one of the first to try it. Every listed skill goes through the trust checks below.

    Security scanned

    Checked by our 8-point scan before listing

    Fresh listing

    Recently published to Agensi

    Money-back guarantee

    Doesn't do what its page promises? You get your money back.

    Trust & safety

    Security scan

    Security scan passed 1 month ago

    Permissions

    No special permissions declared or detected

    Listed1 month ago

    What's inside

    Frequently Asked Questions

    This skill generates professional-grade QA documentation, including test plans, AI-specific risk assessments (like hallucination and injection checks), and UAT scenarios tailored for complex automation workflows. It solves the problem of unstable deployments by ensuring your agents are systematically tested against non-deterministic behaviors and edge cases.

    The QA Pack is model-agnostic and works for any AI agent or automation built on platforms like Make, Zapier, LangChain, or custom API frameworks. It focuses on the logic, tool-calling, and integration points of your workflow rather than the specific code implementation.

    You will receive a comprehensive suite of documentation templates and specialized generators for functional tests, regression packs, defect reports, and business-ready UAT scripts. It also includes a coverage matrix to map your requirements against specific AI and integration test cases.

    Setup is instantaneous; once you provide your automation requirements or system prompts, the skill begins generating structured testing documentation. There is no complex installation required, as it functions as a specialized documentation and logic auditor for your existing workflows.

    Yes, the skill includes a dedicated Regression Pack feature that identifies exactly which tests need to be rerun when you update a system prompt, switch LLM models, or change API permissions. This ensures that new updates don't break existing functionality or introduce new hallucinations.

    New in Agents & Orchestration