Acceptance Criteria Builder

    by Maurice Emberger

    1

    Prüft Akzeptanzkriterien auf Klarheit, Testbarkeit und Vollständigkeit. Liefert priorisierte Lücken, Risiken und konkrete Verbesserungen für Produkt- und Projektteams.

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    Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLIVVS CodeWWindsurfMManus+14 more

    See it in action

    You say

    Create acceptance criteria for a new password reset feature. Context: User forgets password, needs email link. Roles: Registered users. Risk: Token expiration security.

    Your agent does

    Acceptance Criteria

    Scenario: Successful Reset Given a registered user requests a link When they click the valid token in email Then they can set a new password.

    Edge Case: Expired Token Given a token older than 24h When accessed Then show 'Link Expired' error.

    Status: READY

    About this skill

    The problem

    Vague requirements lead to scope creep and missed edge cases during development. Quality assurance often fails because acceptance criteria lack the specificity needed for automated or manual testing.

    What it does

    • Extracts testable criteria, edge cases, and negative tests from confirmed requirements.
    • Separates facts from assumptions to prevent unconfirmed product decisions from leaking into the build.
    • Maps out Happy Path, Error Path, permissions, and side effects for every feature.
    • Performs cross-checks against existing test cases in tests/test-cases.md to ensure consistency.
    • Generates a structured output with Given/When/Then scenarios, risk assessments, and required test data.

    Why this beats prompting it yourself

    Writing bulletproof acceptance criteria is tedious and prone to human oversight regarding edge cases. This skill enforces a strict verification logic that flags missing evidence as BLOCKED, preventing you from starting work on incomplete specs.

    Use cases

    • Transforming rough product notes into formal Given/When/Then acceptance criteria.
    • Identifying technical risks and dependencies before a sprint planning session.
    • Generating edge case test data requirements for QA teams.
    • Reviewing existing requirements against internal test documentation for gaps.

    Known limitations

    Requires structured input including goals, roles, and risks to function effectively. Does not provide legal, medical, or financial advice.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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