AI-DLC is a portable set of skills that applies a decision-driven AI development lifecycle to coding-assistant work. Developers use it to organize requirements, design, tasks, implementation, and verification while keeping humans involved in decisions. The catalogue entries are its workflow skills.
Final integration build and test verification. Validates that implemented code compiles, passes all test suites, and meets quality gates before deployment.
Scan workspace, assess project landscape, and generate context document, blueprints, and platform shim. First phase of the AI-DLC specification workflow.
CI/CD pipeline generation and deployment configuration. Produces pipeline configs, environment definitions, and deployment scripts for the target platform.
Technology decisions and architecture design. Generates D3 decision gate, validates choices, produces modular or compact design documents with components, data model, API spec, integration, implementation, correctness, and NFR specifications.
Translate business needs into user stories with EARS acceptance criteria. Generates decision gate, personas, and requirements. Includes routing recommendation for next phase.
Deep brownfield codebase analysis. Extracts architecture, modules, data models, API surface, business rules, features, integrations, conventions, and technical debt.
Cross-unit design review. Compares design documents across multiple units or modules for conflicts, inconsistencies, and alignment issues. Produces a severity-classified review report with resolution recommendations.
AI-DLC workflow orchestrator. Reads manifest state, dispatches to phase skills, manages rollback and status. Executes phases by loading and following each skill's SKILL.md.
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MIT-0
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: