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Found 1,444 Skills
Production MLOps and ML/LLM/agent security skill for deploying and operating ML systems in production (registry + CI/CD, serving, monitoring/drift, evaluation loops, incident response/runbooks, and governance), including GenAI security (prompt injection, jailbreaks, RAG security, privacy, and supply chain).
Google Cloud Platform CLI (gcloud, gcloud storage, bq). Use when: managing GCP resources, deploying to Cloud Run/Cloud Functions/GKE/App Engine, working with Cloud Storage, BigQuery, IAM, Compute Engine, Cloud SQL, Pub/Sub, Secret Manager, Artifact Registry, Cloud Build, Cloud Scheduler, Cloud Tasks, Vertex AI, VPC/networking, DNS, logging/monitoring, or any GCP service. Also covers: authentication, project/config management, CI/CD integration, serverless deployments, container registry, docker push to GCP, managing secrets, Workload Identity Federation, and infrastructure automation.
Monitoring, logging, and tracing implementation using OpenTelemetry as the unified standard. Use when building production systems requiring visibility into performance, errors, and behavior. Covers OpenTelemetry (metrics, logs, traces), Prometheus, Grafana, Loki, Jaeger, Tempo, structured logging (structlog, tracing, slog, pino), and alerting.
Detects Follow-Through Day (FTD) signals for market bottom confirmation using William O'Neil's methodology. Dual-index tracking (S&P 500 + NASDAQ) with state machine for rally attempt, FTD qualification, and post-FTD health monitoring. Use when user asks about market bottom signals, follow-through days, rally attempts, re-entry timing after corrections, or whether it's safe to increase equity exposure. Complementary to market-top-detector (defensive) - this skill is offensive (bottom confirmation).
Scaffolds or references a production-ready Node.js REST API with Express 5, TypeScript, Mongoose (MongoDB), Redis, Sentry, JWT auth, bcrypt, rate limiting, and centralized error handling. Use when the user wants to start a new observable and resilient backend, needs a Node.js API boilerplate with security and monitoring, or asks to clone or adapt this template repository.
Define and design a product metrics dashboard with key metrics, data sources, visualization types, and alert thresholds. Use when creating a metrics dashboard, defining KPIs, setting up product analytics, or building a data monitoring plan.
Extract structured data from multiple web pages using Playwright with built-in ethical crawling practices including rate limiting, robots.txt compliance, and error monitoring. Use when asked to "scrape data from", "extract information from pages", "collect data from site", "crawl multiple pages", or when gathering structured data from websites. Supports pagination, multi-page extraction, data aggregation, and export to CSV/JSON/Markdown. Works with browser_navigate, browser_evaluate, browser_wait_for, and browser_snapshot tools.
Use this skill when optimizing email deliverability, sender reputation, or authentication. Triggers on SPF record setup, DKIM signing configuration, DMARC policy deployment, IP warm-up planning, bounce handling strategy, sender reputation monitoring, inbox placement troubleshooting, email infrastructure hardening, DNS TXT record configuration for email, and diagnosing why emails land in spam. Acts as a senior email infrastructure advisor for engineers and marketers managing transactional or marketing email.
Interactive MCP visual output via @json-render/mcp. Upgrade plain JSON tool responses to interactive dashboards rendered in sandboxed iframes inside Claude, Cursor, and ChatGPT conversations. Covers createMcpApp(), registerJsonRenderTool(), CSP config, streaming, and dashboard component patterns. Use when building MCP servers that return visual output, upgrading existing MCP tools with interactive UI, or creating eval/monitoring dashboards.
Alibaba Cloud AnalyticDB for MySQL O&M diagnosis assistant. It supports cluster information query, performance monitoring, slow query diagnosis, running SQL analysis, table-level optimization suggestions, etc. Triggers: "ADB MySQL", "AnalyticDB", "cluster list", "slow query", "BadSQL", "data skew", "idle index", "SQL Pattern", "space diagnosis", "table diagnosis", "performance monitoring".
Designs and builds ETL/ELT data pipelines. Takes data sources, destination, transformation requirements. Generates pipeline code (Python/SQL), scheduling config, error handling, monitoring setup, and data quality checks. Outputs data-pipeline-spec.md + implementation files.
When the user wants to assess supplier risks, monitor supplier health, or develop risk mitigation strategies. Also use when the user mentions "supplier risk assessment," "supply chain risk," "business continuity," "supplier monitoring," "supply disruption," "risk scoring," "supplier financial health," or "contingency planning." For initial supplier selection, see supplier-selection. For overall supply chain risk, see risk-mitigation.