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Found 57 Skills
TypeScript, React, and JavaScript best practices enforced by Ultracite/Biome.
Canonical, cross-language clean code standard with stable rule IDs (CC-*). Use when writing/reviewing code, defining team standards, or mapping lint/CI findings to consistent CC-* rule citations.
Setup universal code quality standards in your project. Use when the user wants to generate coding standards files (CLAUDE.md, AGENTS.md, GEMINI.md, etc.) or mentions 'code standards', 'code review setup', or similar intent in any language.
Enforce project code standards when writing code
Complete project planning and execution framework. Automatically includes all 14 planning sections (planning/0-Master-Index.md through planning/13-Lessons-Learned-Continuous-Improvement.md) plus all 9 Claude Skills (tech-stack-selector, architecture-decisions, code-standards-enforcer, ci-cd-pipeline-builder, agile-executor, project-risk-identifier, automation-orchestrator, webapp-testing, web-artifacts-builder). When installed, all planning templates and execution skills are immediately available.
Technology-agnostic blueprint generator for creating comprehensive copilot-instructions.md files that guide GitHub Copilot to produce code consistent with project standards, architecture patterns, and exact technology versions by analyzing existing codebase patterns and avoiding assumptions.
Pragmatic coding standards - concise, direct, no over-engineering, no unnecessary comments
Elite AI/ML Senior Engineer with 20+ years experience. Transforms Claude into a world-class AI researcher and engineer capable of building production-grade ML systems, LLMs, transformers, and computer vision solutions. Use when: (1) Building ML/DL models from scratch or fine-tuning, (2) Designing neural network architectures, (3) Implementing LLMs, transformers, attention mechanisms, (4) Computer vision tasks (object detection, segmentation, GANs), (5) NLP tasks (NER, sentiment, embeddings), (6) MLOps and production deployment, (7) Data preprocessing and feature engineering, (8) Model optimization and debugging, (9) Clean code review for ML projects, (10) Choosing optimal libraries and frameworks. Triggers: "ML", "AI", "deep learning", "neural network", "transformer", "LLM", "computer vision", "NLP", "TensorFlow", "PyTorch", "sklearn", "train model", "fine-tune", "embedding", "CNN", "RNN", "LSTM", "attention", "GPT", "BERT", "diffusion", "GAN", "object detection", "segmentation".
Implement tasks from the change, writing actual code following the specs and design. Trigger: When the orchestrator launches you to implement one or more tasks from a change.
Proxy2.0 Java CRUD Interface Implementation Workflow: A 10-step standard process from requirement to full delivery. Use when: (1) Implementing new CRUD features for an entity, (2) Adding new API endpoints with full stack (DO/Mapper/VO/Service/Controller/SQL), (3) Following the standard implementation workflow for new business entities.
Create distinctive, production-grade frontend interfaces with intentional aesthetics, high craft, and non-generic visual identity. Use when building or styling web UIs, components, pages, dashboards, or frontend applications.
Use when symfony value objects and dtos