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Found 5,098 Skills
Use this skill when building Model Context Protocol (MCP) servers on Cloudflare Workers. This skill should be used when deploying remote MCP servers with TypeScript, implementing OAuth authentication (GitHub, Google, Azure, etc.), using Durable Objects for stateful MCP servers, implementing WebSocket hibernation for cost optimization, or configuring dual transport methods (SSE + Streamable HTTP). The skill prevents 15+ common errors including McpAgent class export issues, OAuth redirect URI mismatches, WebSocket state loss, Durable Objects binding errors, and CORS configuration mistakes. Includes production-tested templates for basic MCP servers, OAuth proxy integration, stateful servers with Durable Objects, and complete wrangler.jsonc configurations. Covers all 4 authentication patterns: token validation, remote OAuth with DCR, OAuth proxy (workers-oauth-provider), and full OAuth provider implementation. Self-contained with Worker and Durable Objects basics. Token efficiency: ~87% savings (40k → 5k tokens). Production tested on Cloudflare's official MCP servers. Keywords: MCP server, Model Context Protocol, cloudflare mcp, mcp workers, remote mcp server, mcp typescript, @modelcontextprotocol/sdk, mcp oauth, mcp authentication, github oauth mcp, durable objects mcp, websocket hibernation, mcp sse, streamable http, McpAgent class, mcp tools, mcp resources, mcp prompts, oauth proxy, workers-oauth-provider, mcp deployment, McpAgent export error, OAuth redirect URI, WebSocket state loss, mcp cors, mcp dcr
A Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Great for exploring relationships between variables and visualizing distributions. Use for statistical data visualization, exploratory data analysis (EDA), relationship plots, distribution plots, categorical comparisons, regression visualization, heatmaps, cluster maps, and creating publication-quality statistical graphics from Pandas DataFrames.
Library for bioinformatics and community ecology statistics. Provides data structures and algorithms for sequences, alignments, phylogenetics, and diversity analysis. Essential for microbiome research and ecological data science. Use for alpha/beta diversity metrics, ordination (PCoA), phylogenetic trees, sequence manipulation (DNA/RNA/Protein), distance matrices, PERMANOVA, and community ecology analysis.
Automatically announces plans, issues, and summaries out loud using TTS. Use this skill PROACTIVELY after completing major tasks like finalizing a plan, resolving an issue, or generating a summary. Each project gets a unique voice so users can identify which project is speaking from another room. Providers fallback in order (google, openai, elevenlabs, say) on rate limits.
Build trading systems in the style of D.E. Shaw, the pioneering computational finance firm. Emphasizes systematic strategies, rigorous quantitative research, and world-class technology infrastructure. Use when building research platforms, systematic trading strategies, or quantitative finance infrastructure.
Build MECE issue trees for complex business problems. Use when you need rigorous problem decomposition, branch prioritization, and a decision-ready analysis backlog.
Azure AD OAuth2/OIDC SSO integration for Kubernetes applications. Use when implementing Single Sign-On, configuring Azure AD App Registrations, restricting access by groups, or integrating tools (DefectDojo, Grafana, ArgoCD, Harbor, SonarQube) with Azure AD authentication.
Generate production-ready web assets through conversation. Favicons, PWA icons, and social media images from logos, emojis, or text.
Score, grade, or evaluate things using AI against a rubric. Use when grading essays, scoring code reviews, rating candidate responses, auditing support quality, evaluating compliance, building a quality rubric, running QA checks against criteria, assessing performance, rating content quality, or any task where you need numeric scores with justifications — not just categories.
Pull structured data from messy text using AI. Use when parsing invoices, extracting fields from emails, scraping entities from articles, converting unstructured text to JSON, extracting contact info, parsing resumes, reading forms, or any task where messy text goes in and clean structured data comes out. Powered by DSPy extraction.
Strategic guidance for operationalizing machine learning models from experimentation to production. Covers experiment tracking (MLflow, Weights & Biases), model registry and versioning, feature stores (Feast, Tecton), model serving patterns (Seldon, KServe, BentoML), ML pipeline orchestration (Kubeflow, Airflow), and model monitoring (drift detection, observability). Use when designing ML infrastructure, selecting MLOps platforms, implementing continuous training pipelines, or establishing model governance.
Plan, launch, and optimize paid advertising campaigns for a solopreneur business. Use when running ads on Google, Facebook, LinkedIn, or other platforms to drive traffic, leads, or sales. Covers platform selection, campaign structure, ad copy and creative, targeting, budget allocation, conversion tracking, and optimization based on performance data. Trigger on "paid ads", "run ads", "Facebook ads", "Google ads", "advertising strategy", "ad campaign", "PPC", "how to advertise".