Full Agent Development Life Cycle pipeline for the aiagent project. Runs story refinement → design → implementation planning (with human approval checkpoint) → implementation → testing → security → database → devops. Each coding phase uses a doer + antagonistic reviewer loop requiring score >= 8/10.
Create a detailed user story for the aiagent project with acceptance criteria and technical breakdown. Uses the story-refiner agent to explore the codebase and produce a structured story artifact.
Database schema + review loop for the aiagent project. The dba agent designs schema changes ensuring JSON/MongoDB storage duality, then the dba-reviewer scores the changes against the 6 pillars. Loops until score >= 8/10 or 3 iterations maximum.
Deployment readiness check for the aiagent project. Verifies the release pipeline, Docker build, and all 7 binary targets are ready before tagging a release. Uses the devops agent.
Architecture design + review loop for the aiagent project. The architect designs a solution following DDD patterns, then the architect-reviewer scores it against the 6 pillars. Loops until score >= 8/10 or 3 iterations maximum.
DevOps pipeline + review loop for the aiagent project. The devops agent manages CI/CD and Docker changes, then the devops-reviewer scores against the 6 pillars. Loops until score >= 8/10 or 3 iterations maximum.
Code implementation + review loop for the aiagent project. The developer implements changes following the approved plan, then the developer-reviewer scores the code against the 6 pillars including a mandatory duplication check. Loops until score >= 8/10 or 3 iterations maximum.
Break a feature or epic into ordered, implementable user stories for the aiagent project. Uses the planner agent to analyze the feature and produce a sprint plan with story dependencies.