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Export trained PyTorch models to various formats (ONNX, TorchScript, TensorRT) and upload to model registries (Hugging Face Hub, MLflow). Use when deploying models, sharing trained weights, or preparing for production inference.

Install Remotion, set up Remotion, add Remotion to a project, install Remotion AI skills, update Remotion, upgrade Remotion packages, check Remotion version, set up video project with Remotion, remotion skills, remotion rules

Service-profile-driven project audit. Auto-fires when the user requests audit, review, code review, pre-launch check, security audit, OWASP/SOLID/12-Factor compliance, project skeleton/bootstrap/setup, or any equivalent in any language (e.g., 점검, 감사, 리뷰, 출시 전 검토, 보안 점검, 골조, 셋업). Reads the full 0–10 section checklist from SPEC.md, filters items by grade (🔴🟠🟡🔵⚪) against the user's service profil

Use when implementing features, refactors, or multi-file changes. Orchestrated plan-then-execute with subagent dispatch and regression checkpoints.

Паттерн Schema-Guided Reasoning (SGR) для решения задач на базе LLM с использованием structured output, constrained decoding, Pydantic моделей. Используй когда нужно: структурированный вывод, JSON schema, воспроизводимость рассуждений, тестируемость промежуточных шагов, направленное рассуждение модели, response_format, parse().

Enforces Karpathy's 4 LLM-coding principles (Think Before Coding, Simplicity First, Surgical Changes, Goal-Driven Execution). Auto-fires whenever the user requests writing, editing, refactoring, fixing, or adding code. Blocks drive-by refactoring, over-engineering, and speculative changes; demands clarification before implementation, minimum code, surgical edits, and conversion of tasks into verif

Application security agent that audits code for OWASP Top 10 vulnerabilities, hardcoded secrets, and common security flaws. Triggers on: security audit, vulnerability scan, OWASP check, security review, penetration test, hardening.

Building professional CLIs with Typer and Rich - type-safe argument parsing, progress bars, model visualization, Hydra integration, RichHandler logging, and multi-process handling for ML workflows

Use after completing any code implementation, bug fix, or refactor. Structured review with pass/fail verification before declaring done.

Транскрипция и суммаризация митингов, созвонов, встреч по аудио/видео файлу. Используй когда: summarize meeting, транскрибировать созвон, обработать аудио митинга, summary встречи, суммаризация записи, meeting summary, транскрипция.

PR レビューコメント・ローカルファイル・会話内のレビュー結果からフィードバックを読み取り、コードに反映する。ユーザーが「レビュー反映して」「フィードバック適用」「/smart-review-apply」と言ったら起動する。

Manage ML experiments, track results, and compare performance across different configurations. Use when setting up experiment tracking, creating experiment configs, comparing runs, or analyzing experiment results with W&B, TensorBoard, or MLflow.