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Found 1,437 Skills
Guide the design and implementation of order lifecycle management in trading systems. Use when building an order state machine for an OMS or EMS, implementing or debugging FIX protocol connectivity to exchanges, handling cancel/replace race conditions, defining pre-submission validation rules (buying power, position limits, restricted lists), selecting order types and time-in-force instructions, designing multi-leg or OCO or bracket orders, building CAT-compliant audit trails, troubleshooting order rejections or unexpected state transitions, hardening an OMS against edge cases, or implementing order persistence and recovery for failover. Also covers FIX message flows, ClOrdID chaining, and partial fill aggregation.
Use when creating or developing, before writing code or implementation plans - refines rough ideas into fully-formed designs through collaborative questioning, alternative exploration, and incremental validation. Don't use during clear 'mechanical' processes
Parse and analyze email headers to trace the origin of phishing emails, verify sender authenticity, and identify spoofing through SPF, DKIM, and DMARC validation.
Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like "make me a GIF of X doing Y for Slack."
Invoke a Rubber Duck Reviewer subagent to independently critique plans and implementations before proceeding. Use when the agent is about to implement a non-trivial plan (multi-file changes, architectural decisions, security-sensitive logic, database schema changes), after completing a self-contained unit of work (module, endpoint, feature), when stuck or facing repeated failures (same test fails 2+ times, unexpected results), or when the agent wants independent validation of assumptions and design decisions. Triggers on any non-trivial implementation task where independent critique would catch blind spots before they become costly mistakes.
Use when the user wants to set up, scale, validate, or harden NVIDIA physical AI infrastructure for synthetic data generation workflows across local MicroK8s or Azure AKS, including Kubernetes clusters, inference endpoint deployment, OSMO deployment, workload submission readiness, and infrastructure failure recovery. Trigger keywords: physical ai infrastructure, resilient scaling, SDG infrastructure, microk8s, azure aks, NVCF deployment, NIM Operator, OSMO deploy, workflow scaling. Don't trigger for: OSMO log summarization or workload-only operations unless infrastructure setup, scaling, validation, or recovery is requested.
Used for smoke or dataset finetuning of NV-Segment-CT VISTA3D on CT NIfTI labels. Not for clinical validation.
Expert cuTile programming assistant. Write high-performance GPU kernels using cuTile's tile-based programming model with proper validation and optimization. Supports deep agent orchestration for complex multi-kernel tasks.
HarmonyOS code review skill for auditing ArkTS projects against official Huawei development guidelines and security best practices. Use when reviewing HarmonyOS applications for: (1) Security compliance (hardcoded credentials, encryption, input validation), (2) ArkTS language standards (hilog usage, type safety, magic numbers), (3) Component lifecycle management (resource cleanup, event subscription handling), (4) State management (V1/V2 decorator consistency), (5) Database operations (ResultSet handling, transaction management, encryption), (6) Permission management (official permission patterns), (7) Performance issues (async forEach, resource leaks), (8) API version compatibility, (9) Kit usage best practices. Generates comprehensive markdown reports with prioritized fix recommendations.
Integrate a HuggingFace Computer Vision model into the NVIDIA TAO Toolkit ecosystem (tao-core config, tao-pytorch trainer, tao-deploy TensorRT pipeline). Use when the user asks to "integrate a HuggingFace model into TAO", "add an HF model to TAO Toolkit", "wire a HuggingFace ViT/DETR/ SegFormer into tao-pytorch", "build a TAO trainer + deploy pipeline for an HF CV model", or pastes a HuggingFace model URL/ID and wants it turned into a TAO model. Covers the full 7-phase loop: prerequisites check, HuggingFace inspection and validation, codebase exploration, tao-core configuration and native trainer implementation, ONNX export plus TensorRT deploy integration, packaging and L0 testing, container-based end-to-end validation, and (conditional) accuracy/latency tuning. Supports classification, object detection, semantic / instance / panoptic segmentation, zero-shot detection, and depth estimation.
Create Product Requirements Documents (PRD) following SDD methodology - Layer 2 artifact defining product features and user needs
Use when implementing a planned OpenSpec change by applying tasks and validating all artifacts.