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Found 102 Skills
Only to be triggered by explicit /parallel-task-spark commands.
Writes failing tests first for test-driven development and hands off a strict implementation contract that requires agents to make those tests pass without weakening the tests. Use when users ask for test-first workflows, RED/GREEN cycles, or behavior-gating tasks with automated tests.
Spawn Codex subagents via background shell to offload context-heavy work. Use for: deep research (3+ searches), codebase exploration (8+ files), multi-step workflows, exploratory tasks, long-running operations, documentation generation, or any other task where the intermediate steps will use large numbers of tokens.
Generate MDX blog posts or recaps from session logs in `sessions/articles`. Use when the user asks to turn daily session notes into publishable blog posts, define writing style or linking rules for those posts, or produce MDX drafts that follow the project's standards and file location.
SSH into an Ubuntu VPS (Docker) for a read-only health/security/update report (UFW + fail2ban) and propose fixes; apply updates/restarts only with explicit confirmation. Use when the user wants a read-only VPS health/security check.
Review and design SaaS/product marketing sites and frontend interfaces end-to-end: clarify value, fix hierarchy, and implement distinctive, production-grade UI that avoids generic AI aesthetics.
Expertise senior/lead React developer 20 tahun dengan TanStack ecosystem (Query, Router, Table, Form, Start). Gunakan skill ini ketika: (1) Membuat aplikasi React dengan TanStack libraries, (2) Review/refactor kode React untuk clean code, (3) Debugging React/TanStack issues, (4) Setup project structure yang maintainable, (5) Optimasi performa React apps, (6) Memilih library yang tepat untuk use case tertentu, (7) Mencegah common bugs dan memory leaks, (8) Implementasi best practices KISS dan less is more. Trigger keywords: React, TanStack, React Query, TanStack Router, TanStack Table, TanStack Form, TanStack Start, Vinxi, clean code, refactor, performance, debugging.
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".
Generate nested AGENTS.md coding guidelines per module (monorepo-aware), detect languages/tooling, ask architecture preferences, and set up missing formatters/linters (Spotless for JVM). Use when the user wants module-scoped AGENTS.md coding guidelines or to set up missing formatters/linters.
Triage customer support tickets/emails/chats into categories, priority, and next action; draft responses and create reproducible steps; use for Zendesk/Intercom/Help Scout exports or pasted threads.
Plan work before coding: do repo research, analyze options/risks, and ask clarifying questions before proposing an implementation plan. Use when the user asks for a plan, design/approach, scope breakdown, or implementation steps.
Production-grade mobile app development with Swift (iOS), Kotlin (Android), React Native, and WebView patterns, including UI/UX, navigation, state management, networking, local storage, push notifications, and App Store deployment.