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Found 522 Skills
Build and deploy applications on inference.sh. Use when getting started, understanding the platform, creating apps, configuring resources, or needing an overview of inference.sh app development. Supports both Python and Node.js. Triggers: inference.sh app, belt app, inf.yml, inference.py, inference.js, deploy app, app development, build app, create app, GPU app, VRAM, app resources, app secrets, app integrations, multi-function app
Manages MongoDB Atlas Stream Processing (ASP) workflows. Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations for streaming data workloads and event processing. NOT for general MongoDB queries or Atlas cluster management. Requires MongoDB MCP Server with Atlas API credentials.
Start Here. Use when the user asks about Narev Cloud, the Pricing API, model pricing (API reference skill vs applied workflows on top of that API), live LLM pricing, token costs, cost calculation, pinning or snapshotting model rates, Narev SDK, @ai-billing/core, provider middleware packages, Vercel AI SDK billing, Next.js App Router route handlers, framework-specific billing patterns, usage-based billing, billing integrations (Polar, Stripe, Lago, OpenMeter), FOCUS format, Narev Self-Hosted (ThinOps), deployment, COGS, customer tagging, FinOps for AI, or this documentation site. Guides you to the right skill or documentation path based on their task.
Use when developing Salesforce applications, Apex code, Lightning Web Components, SOQL queries, triggers, integrations, or CRM customizations. Invoke for governor limits, bulk processing, platform events, Salesforce DX.
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.
Python backend development expertise for FastAPI, security patterns, database operations, Upstash integrations, and code quality. Use when: (1) Building REST APIs with FastAPI, (2) Implementing JWT/OAuth2 authentication, (3) Setting up SQLAlchemy/async databases, (4) Integrating Redis/Upstash caching, (5) Refactoring AI-generated Python code (deslopification), (6) Designing API patterns, or (7) Optimizing backend performance.
Debug MCP server communication. Use for troubleshooting MCP integrations, viewing traffic, and analyzing latency.
Use MCP servers on-demand via the mcp CLI tool - discover tools, resources, and prompts without polluting context with pre-loaded MCP integrations
Use this skill when building MCP (Model Context Protocol) servers with TypeScript on Cloudflare Workers. This skill provides production-tested patterns for implementing tools, resources, and prompts using the official @modelcontextprotocol/sdk. It prevents 10+ common errors including export syntax issues, schema validation failures, memory leaks from unclosed transports, CORS misconfigurations, and authentication vulnerabilities. This skill should be used when developers need stateless MCP servers for API integrations, external tool exposure, or serverless edge deployments. For stateful agents with WebSockets and persistent storage, consider the Cloudflare Agents SDK instead. Supports multiple authentication methods (API keys, OAuth, Zero Trust), Cloudflare service integrations (D1, KV, R2, Vectorize), and comprehensive testing strategies. Production tested with token savings of ~70% vs manual implementation. Keywords: mcp, model context protocol, typescript mcp, cloudflare workers mcp, mcp server, mcp tools, mcp resources, mcp sdk, @modelcontextprotocol/sdk, hono mcp, streamablehttpservertransport, mcp authentication, mcp cloudflare, edge mcp server, serverless mcp, typescript mcp server, mcp api, llm tools, ai tools, cloudflare d1 mcp, cloudflare kv mcp, mcp testing, mcp deployment, wrangler mcp, export syntax error, schema validation error, memory leak mcp, cors mcp, rate limiting mcp
Use when building secure AI pipelines or hardening LLM integrations. Defense-in-depth implements 8 validation layers from edge to storage with no single point of failure.
Create and execute temporary scripts (Python, Node.js, shell) during workflow execution for API integrations, data processing, and custom tools. Use when user needs to interact with external APIs, process data with specific libraries, or create temporary executable code.
Model Context Protocol expert for building MCP servers, tools, resources, and client integrationsUse when "mcp server, model context protocol, claude code extension, building ai tools, tool definition, mcp transport, stdio transport, sse transport, resource provider, prompt template, mcp, model-context-protocol, claude-code, ai-tools, llm-integration, anthropic, server, protocol" mentioned.