CMMI-based SDLC framework (Levels 2-4) with GitHub/Azure DevOps integration (8 skills, 4 agents) - comprehensive process guidance for high-quality software development with specialist support for architecture decisions, quality assurance, bug triage, and process routing
Use when making architecture decisions, setting up CI/CD, managing technical debt, or choosing branching strategies - enforces ADR requirements and prevents resume-driven design
Use when making architectural decisions without documentation, skipping risk analysis, accepting risks without mitigation, or treating governance as optional bureaucracy - enforces mandatory DAR/RSKM based on project risk level
Use when starting new projects with CMMI, adding CMMI to active development, preparing for audits, migrating tools, or facing team resistance to process adoption
Use when implementing CMMI processes in GitHub or Azure DevOps, migrating between platforms, or establishing traceability/compliance on GitHub/Azure - platform-specific process guidance
Use when deciding test strategy, struggling with code reviews, shipping without tests, or conflating verification with validation
Use when establishing measurement programs, analyzing metrics with statistical process control, setting baselines, or implementing CMMI Level 4 quantitative management - prevents vanity metrics and measurement theater
Use when defining requirements, tracking traceability, managing requirement changes, or establishing RTM - covers elicitation, analysis, specification across CMMI Levels 2-4
Use when users request SDLC guidance, CMMI processes, requirements management, design documentation, quality assurance, governance, metrics, or adopting processes on existing projects
Deep codebase architecture analysis (4 commands, 2 agents) - C4 diagrams, subsystem catalogs, security surface mapping, test infrastructure analysis, dependency visualization, incremental delta analysis, cross-pack specialist integration
TDD-validated architectural assessment enforcing professional discipline - prevents diplomatic softening, analysis paralysis, and security priority compromise - 3 specialist skills + router
Web backend development expertise across FastAPI, Django, Express, REST/GraphQL APIs, microservices, and production deployment patterns - router + specialist skills for modern web APIs
DevOps and deployment automation expertise - CI/CD pipeline architecture, deployment strategies, zero-downtime deployments, and infrastructure reliability patterns - TDD-validated with RED-GREEN-REFACTOR testing
Universal software engineering methodology - systematic debugging, safe refactoring, code review, incident response, technical debt triage, codebase confidence building - 6 language-agnostic skills
TDD-validated implementation planning with comprehensive anti-rationalization defenses - atomic task breakdown, complete code examples, exact file paths - 1 skill with test scenarios
Game simulation implementation patterns and tactics - 11 skills
Emergent gameplay and systemic game design - 9 skills
UX design fundamentals - visual design, accessibility, interaction patterns - 11 skills
Systematic maintenance and enhancement of skill packs through investigative domain analysis, RED-GREEN-REFACTOR testing, and automated quality improvements
SME (Subject Matter Expert) Agent Protocol - mandatory protocol for all specialist agents defining fact-finding, output contracts, and confidence/risk assessment
Documentation structure, clarity, security-aware docs - 9 technical writing skills
No verified skills in this plugin.
E2E testing, performance testing, chaos engineering, test automation - 21 quality engineering skills
Threat modeling, security controls, compliance, ATO - 9 comprehensive security skills
No verified skills in this plugin.
Primary router for all AI/ML engineering skillpacks - directs to specialized packs
Reinforcement learning - DQN, PPO, SAC, reward shaping, exploration - 13 skills
Dynamic/morphogenetic neural networks - grow, prune, adapt topology during training. Continual learning, gradient isolation, modular composition, lifecycle orchestration - 6 skills, 1 agent, 2 commands
LLM techniques - fine-tuning, RLHF, inference optimization - 8 skills
Production ML - quantization, serving, MLOps, monitoring, debugging - 11 skills
Neural architectures - CNNs, Transformers, RNNs, selection guidance - 9 skills
PyTorch mastery - tensors, modules, distributed training, profiling - 9 skills
Game simulation mathematics - ODEs, stability, control theory - 9 skills
Systems thinking methodology - patterns, leverage points, archetypes, modeling, visualization - 6 TDD-validated skills
Modern Python 3.12+ engineering: types, testing, async, scientific computing, ML workflows - 10 skills
Training stability - optimizers, learning rates, convergence, debugging - 11 skills