Library of reusable skills to empower AI agents. From planning to deployment, each skill solves a specific problem.
9 skills available
Force requirement clarification before technical design. Prevents architectures solving the wrong problem.
Use Case
Before any new implementation
@skill clarify-first 
Automatic generation of C4/UML diagrams from existing code. Visualize the real architecture.
Use Case
Onboarding, technical documentation
@skill architecture-diagrams 
Reverse-engineering of undocumented architecture to complete C4 model with context, containers, and components.
Use Case
Legacy systems, audits
@skill c4-model-generator 
DDD design with bounded contexts, aggregates, and entities. Establishes the ubiquitous language of the project.
Use Case
New domains, large refactors
@skill design-domain-model 
Analysis and visualization of data schemas. Detects relationships, anomalies, and normalization opportunities.
Use Case
Migrations, DB optimization
@skill data-model-explorer 
Strict YAGNI/KISS enforcement. Challenges premature abstractions and simplifies before scaling.
Use Case
Code reviews, design decisions
@skill avoid-overengineering 
Minimalist scaling strategies. Prioritizes simple solutions before complex infrastructure.
Use Case
Startups, MVPs
@skill lean-scaling-low-profile 
Comprehensive production readiness checklist: logging, monitoring, backups, rollback.
Use Case
Pre-launch, deployments
@skill production-readiness 
Reactive state patterns (Signals, Observables, Stores). Predictable state management in frontends.
Use Case
SPAs, complex apps
@skill reactive-state-management 
@skill clarify-first The agent reads the skill automatically
The skill guides the behavior