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Found 1,444 Skills
Comprehensive Kubernetes and OpenShift cluster management skill covering operations, troubleshooting, manifest generation, security, and GitOps. Use this skill when: (1) Cluster operations: upgrades, backups, node management, scaling, monitoring setup (2) Troubleshooting: pod failures, networking issues, storage problems, performance analysis (3) Creating manifests: Deployments, StatefulSets, Services, Ingress, NetworkPolicies, RBAC (4) Security: audits, Pod Security Standards, RBAC, secrets management, vulnerability scanning (5) GitOps: ArgoCD, Flux, Kustomize, Helm, CI/CD pipelines, progressive delivery (6) OpenShift-specific: SCCs, Routes, Operators, Builds, ImageStreams (7) Multi-cloud: AKS, EKS, GKE, ARO, ROSA operations
Provides NodeReal MegaNode blockchain infrastructure APIs for 25+ chains including BSC, Ethereum, opBNB, Optimism, Polygon, Arbitrum, and Klaytn. Covers standard JSON-RPC endpoints, Enhanced APIs (nr_ methods for ERC-20 token balances, NFT holdings, asset transfers), MegaFuel gasless transactions via BEP-322 paymaster, Direct Route MEV protection, Debug/Trace APIs, WebSocket subscriptions, ETH Beacon Chain consensus layer, Portal API usage monitoring, API Marketplace (NFTScan, Contracts API, SPACE ID, Greenfield, BNB Staking, PancakeSwap, zkSync), non-EVM chains (Aptos, NEAR, Avalanche), and JWT authentication. Use when building blockchain dApps with NodeReal, querying token or NFT data, setting up RPC infrastructure, configuring gasless transactions, protecting against MEV, tracing transactions, verifying smart contracts, resolving .bnb domains, or monitoring validators and API usage.
Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.
System administration expert for Linux, macOS, Windows, services, and monitoring
Use when user asks about blockchain data or building Web3 applications — token balances, NFT ownership, transaction history, ENS resolution, on-chain statistics, JSON-RPC calls, webhooks, real-time monitoring, or any Nodit API integration across EVM, Solana, Sui, Aptos, and other chains
Execute a complete tax-loss harvesting workflow from candidate identification through post-harvest monitoring. Use when the user asks about finding TLH candidates, gain/loss budgeting, replacement security selection, wash-sale compliance, or harvest execution planning. Also trigger when users mention 'unrealized losses in my portfolio', 'swap ETFs for tax purposes', 'harvest losses before year-end', 'substantially identical security', 'wash-sale window', 'NIIT offset', 'loss carryforward', or ask how much tax they can save by harvesting.
Describes how blockchain analytics platforms work in practice, typical use cases (markets, compliance, law enforcement, tax, market integrity), tool layers like visualizers and tracers, and limitations of heuristic attribution. Use when the user asks about blockchain analytics for AML, transaction monitoring, forensic tracing, institutional ops, or taint-style analysis at a high level.
Mitigation patterns for privileged-access and governance-adjacent DeFi failures, anchored on the public Drift Protocol incident analysis in Chainalysis’s blog—social engineering, Solana durable nonces, oracle and collateral abuse, multisig governance, and operational monitoring. Use when hardening signer processes, reviewing admin surfaces, or teaching post-incident lessons—not for designing exploits or attributing actors without evidence.
When the user wants to optimize maintenance strategies, improve equipment reliability, reduce downtime, or implement predictive maintenance. Also use when the user mentions "preventive maintenance," "predictive maintenance," "TPM," "Total Productive Maintenance," "MTBF," "MTTR," "reliability analysis," "equipment maintenance," "condition monitoring," "CBM," "failure analysis," or "spare parts optimization." For quality improvements, see quality-management. For OEE, see lean-manufacturing.
Grafana Cloud cost management — usage monitoring, cost attribution by label, usage alerts, invoice management, and optimization strategies. Covers Adaptive Metrics (cardinality reduction), Adaptive Logs (log filtering), cost attribution labels, and the FOCUS-compliant billing application. Use when analyzing Grafana Cloud spending, setting up cost alerts, attributing costs to teams, reducing metric/log cardinality, or forecasting observability budgets.
Enthu.AI platform help — contact center conversation intelligence with auto QA scorecards, agent coaching, compliance monitoring, and speech analytics. Use when setting up Enthu.AI QA scorecards for call center agents, calls not being scored or transcribed correctly, agents not seeing coaching insights from their calls, Enthu.AI integration with Aircall or RingCentral not syncing, comparing Enthu.AI vs Gong or CallMiner for contact center QA, or configuring sentiment analysis and keyword tracking. Do NOT use for building a general coaching program (use /sales-coaching) or reviewing a specific call transcript (use /sales-call-review).
Builds, configures, debugs, and optimizes AWS observability using CloudWatch (Logs Insights, Metrics, Alarms, Dashboards, EMF), X-Ray, CloudTrail, and ADOT. Covers Log Insights query syntax (fields, filter, stats, parse, pattern, join, subqueries), alarm configuration (metric, composite, anomaly detection, missing data treatment), dashboard design, custom metrics (PutMetricData, EMF, metric filters), X-Ray tracing (ADOT, sampling rules, annotations vs metadata), ADOT collector config, and CloudTrail auditing. Use when the user mentions CloudWatch, Log Insights, alarms, INSUFFICIENT_DATA, dashboards, custom metrics, EMF, X-Ray, traces, sampling, CloudTrail, who deleted, ADOT, OpenTelemetry, observability, monitoring, synthetics, canaries, or troubleshooting alarm behavior. Do NOT use for application logging setup, container log drivers, or security threat detection.