Run acceptance tests using AAID's Three-Layer Model (Gherkin โ DSL โ Protocol Driver) and validate them against quality criteria for architecture, isolation, and stubbing.
AAID (Augmented AI Development) - BDD/ATDD acceptance testing workflow using the Three-Layer Model where the developer maintains architectural control and reviews all AI-generated code. Use when the user initiates acceptance testing or references AAID BDD. Trigger phrases include: "start BDD", "begin ATDD", "acceptance testing", "acceptance test", "three-layer model", "executable spec", "transform BDD scenarios", "BDD scenarios", "protocol driver", "phase 1", "phase 2", "phase 3", "DSL layer". Also activate when user provides BDD scenarios and asks for executable specifications, or when currently in an active BDD/ATDD cycle that hasn't completed. Do NOT activate for general programming questions, architecture discussions, context sharing, unit-test/TDD work, or presentation-only changes.
Validate acceptance tests against AAID BDD quality criteria. Scans for proper three-layer architecture, isolation patterns, state management, and stubbing practices. Produces pass/warn/fail table with specific findings. Do NOT activate for writing new tests, running tests, or general testing questions.
Own this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimOwn this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Implan: structured planning workflow with companion skills for exploratory spikes and post-execution retros. Produces self-contained plan directories a fresh agent can pick up cold.
AAID (Augmented AI Development) - TDD workflow enforcing disciplined RED/GREEN/REFACTOR cycles with developer-maintained architectural control
Test-quality skills for Claude Code. Currently includes AI-driven mutation testing where Claude acts as the mutation engine, identifying weak tests by mutating source code and tracking which mutants survive.
npx claudepluginhub dawid-dahl-umain/augmented-ai-development --plugin aaid-bddAAID (Augmented AI Development) - TDD workflow enforcing disciplined RED/GREEN/REFACTOR cycles with developer-maintained architectural control
Acceptance Test Driven Development for Claude Code. Enforces the ATDD methodology: write Given/When/Then specs first, generate a project-specific test pipeline, maintain two test streams (acceptance + unit). Inspired by Robert C. Martin's acceptance test approach from empire-2025.
AI test generation with Ralph-loop quality gate: coder โ reviewer โ iterate
Code transformation: Dev SDLC orchestrator (code-shipping pipeline), plan, assert, audit, review, test, refactor, debug, for-sure. Hosts engineering agents.
Document Driven Development โ a structured workflow for AI-assisted software development with TDD, specs, and cross-review
Comprehensive feature development workflow with specialized agents for codebase exploration, architecture design, and quality review