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Found 1,764 Skills
Implement Antithesis workloads by turning the property catalog into SDK assertions and test commands, then refine coverage after triage.
Implements and debugs browser Prompt API integrations in JavaScript or TypeScript web apps. Use when adding LanguageModel availability checks, session creation, prompt or promptStreaming flows, structured output, download progress UX, or iframe permission-policy handling. Don't use for server-side LLM SDKs, REST AI APIs, or non-browser providers.
DataWorks data development Skill. Create, configure, validate, deploy, update, move, and rename nodes and workflows. Manage components, file resources, and UDF functions. Covers 150+ node types: Shell, SQL, Python, DI, Flink, EMR, etc. Supports scheduled and manual workflow orchestration via aliyun CLI or Python SDK. WARNING: Supports mutating operations (Move, Rename) requiring explicit user confirmation. Delete operations are NOT supported by this skill. Triggers: DataWorks, data development nodes, workflows, FlowSpec, scheduling tasks, data integration, ETL pipelines, .spec.json. Also triggers for Alibaba Cloud data development, scheduling node configuration, FlowSpec format, or DI task orchestration.
Infrastructure as code with OpenTofu (open-source Terraform fork) and Pulumi. Covers OpenTofu HCL syntax, providers, resources, data sources, modules, state management with remote backends, workspaces, importing existing infrastructure, plan/apply workflow, variable management, output values, provisioners, and state encryption (OpenTofu-exclusive). Includes Pulumi TypeScript/Python SDKs, stack management, component resources, config/secrets, state backends, policy as code, and automation API. Common patterns for multi-environment setups, module composition, CI/CD integration, drift detection, and secret management. Use when writing or reviewing HCL configurations, managing cloud infrastructure state, migrating from Terraform to OpenTofu, building Pulumi programs in TypeScript or Python, setting up multi-environment IaC pipelines, or implementing state encryption.
Create MCP servers using the C# SDK and .NET project templates. Covers scaffolding, tool/prompt/resource implementation, and transport configuration for stdio and HTTP. USE FOR: creating new MCP server projects, scaffolding with dotnet new mcpserver, adding MCP tools/prompts/resources, choosing stdio vs HTTP transport, configuring MCP hosting in Program.cs, setting up ASP.NET Core MCP endpoints with MapMcp. DO NOT USE FOR: debugging or running existing servers (use mcp-csharp-debug), writing tests (use mcp-csharp-test), publishing or deploying (use mcp-csharp-publish), building MCP clients, non-.NET MCP servers.
OpenTelemetry with Grafana stack. Covers OTel SDK instrumentation for Go/Java/Python/Node.js/.NET, OTLP protocol and endpoint configuration, sending telemetry to Grafana Cloud via OTLP endpoint, Grafana Alloy as OTel collector, sampling strategies, Kubernetes OTel Operator, and migration from other observability tools. Use when instrumenting apps with OTel, configuring OTLP endpoints, setting up collectors, or migrating to OpenTelemetry.
Run cross-framework agent comparisons using evaluatorq from orqkit — compares any combination of agents (orq.ai, LangGraph, CrewAI, OpenAI Agents SDK, Vercel AI SDK) head-to-head on the same dataset with LLM-as-a-judge scoring. Use when comparing agents, benchmarking, or wanting side-by-side evaluation. Do NOT use when comparing only orq.ai configurations with no external agents (use run-experiment instead).
Stellar dApp / frontend development. Covers the JavaScript stellar-sdk (browser + Node.js), Freighter wallet, Stellar Wallets Kit (multi-wallet), Wallet Standard, smart accounts with passkeys, transaction building / signing / submission, Soroban contract invocation from the client, simulation, and error handling. Use when building a React/Next.js/Node.js app that talks to Stellar or Soroban.
Find working Deepgram integration examples with third-party platforms and frameworks. Use whenever someone wants to integrate Deepgram with Twilio, LiveKit, LangChain, Vercel AI SDK, Discord, Vonage, Pipecat, Expo, FastAPI, Cloudflare Workers, Slack, Telegram, LlamaIndex, Zoom, Next.js, Nuxt, Django, SvelteKit, NestJS, Spring Boot, CrewAI, Riverside, SignalWire, and more. Examples are full runnable integration demos, not minimal feature snippets.
This skill provides project-specific coding conventions, architectural principles, repository structure standards, testing patterns, and contribution guidelines for the better-chatbot project (https://github.com/cgoinglove/better-chatbot). Use this skill when contributing to or working with better-chatbot to understand the design philosophy and ensure code follows established patterns. Includes: API architecture deep-dive, three-tier tool system (MCP/Workflow/Default), component design patterns, database repository patterns, architectural principles (progressive enhancement, defensive programming, streaming-first), practical templates for adding features (tools, routes, repositories). Use when: working in better-chatbot repository, contributing features/fixes, understanding architectural decisions, following server action validators, implementing tools/workflows, setting up Playwright tests, adding API routes, designing database queries, building UI components, handling multi-AI provider integration Keywords: better-chatbot, chatbot contribution, better-chatbot standards, chatbot development, AI chatbot patterns, API architecture, three-tier tool system, repository pattern, progressive enhancement, defensive programming, streaming-first, compound component pattern, Next.js chatbot, Vercel AI SDK chatbot, MCP tools, workflow builder, server action validators, tool abstraction, DAG workflows, shared business logic, safe() wrapper, tool lifecycle
Complete guide for Google Gemini API using the CORRECT current SDK (@google/genai v1.27+, NOT the deprecated @google/generative-ai). Covers text generation, multimodal inputs (text + images + video + audio + PDFs), function calling, thinking mode, streaming, and system instructions with accurate 2025 model information (Gemini 2.5 Pro/Flash/Flash-Lite with 1M input tokens, NOT 2M). Use when: integrating Gemini API, implementing multimodal AI applications, using thinking mode for complex reasoning, function calling with parallel execution, streaming responses, deploying to Cloudflare Workers, building chat applications, or encountering SDK deprecation warnings, context window errors, model not found errors, function calling failures, or multimodal format errors. Keywords: gemini api, @google/genai, gemini-2.5-pro, gemini-2.5-flash, gemini-2.5-flash-lite, multimodal gemini, thinking mode, google ai, genai sdk, function calling gemini, streaming gemini, gemini vision, gemini video, gemini audio, gemini pdf, system instructions, multi-turn chat, DEPRECATED @google/generative-ai, gemini context window, gemini models 2025, gemini 1m tokens, gemini tool use, parallel function calling, compositional function calling
Core Pluggy integration patterns and best practices. Use when setting up Pluggy SDK, implementing Connect Widget, managing Items, or configuring webhooks.