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Found 1,764 Skills
Sets up and operates Airbyte Agent Connectors — strongly typed Python packages for accessing 51+ third-party SaaS APIs through a unified entity-action interface. Supported services include Salesforce, HubSpot, Stripe, GitHub, Slack, Jira, Shopify, Zendesk, Google Ads, Notion, Linear, Intercom, Gong, and 36 more connectors spanning CRM, billing, payments, e-commerce, marketing, analytics, project management, helpdesk, developer tools, HR, and communication platforms. Make sure to use this skill when the user wants to connect to any SaaS API, install an airbyte-agent connector package, integrate third-party service data into a Python application or AI agent, query or search records from any supported service, or configure Airbyte MCP tools for Claude. Covers Platform Mode (Airbyte Cloud) and OSS Mode (local Python SDK).
Migrate an MSTest v3 test project to MSTest v4. Use when user says "upgrade to MSTest v4", "update to latest MSTest", "MSTest 4 migration", "MSTest v4 breaking changes", "MSTest v4 compatibility", or has build errors after updating MSTest packages from 3.x to 4.x. Also use for target framework compatibility (e.g. net6.0/net7.0 support with MSTest v4). USE FOR: upgrading MSTest packages from 3.x to 4.x, fixing source breaking changes (Execute -> ExecuteAsync, CallerInfo constructor, ClassCleanupBehavior removal, TestContext.Properties, Assert API changes, ExpectedExceptionAttribute removal, TestTimeout enum removal), resolving behavioral changes (TreatDiscoveryWarningsAsErrors, TestContext lifecycle, TestCase.Id changes, MSTest.Sdk MTP changes), handling dropped TFMs (net5.0-net7.0 dropped, only net8.0+, net462, uap10.0 supported). DO NOT USE FOR: migrating from MSTest v1/v2 to v3 (use migrate-mstest-v1v2-to-v3 first), migrating between test frameworks, or general .NET upgrades unrelated to MSTest.
Configure OpenTelemetry distributed tracing, metrics, and logging in ASP.NET Core using the .NET OpenTelemetry SDK. Use when adding observability, setting up OTLP exporters, creating custom metrics/spans, or troubleshooting distributed trace correlation.
Build a composable CLI for Codex from API docs, an OpenAPI spec, existing curl examples, an SDK, a web app, an admin tool, or a local script. Use when the user wants Codex to create a command-line tool that can run from any repo, expose composable read/write commands, return stable JSON, manage auth, and pair with a companion skill.
Dollar Cost Averaging (DCA) for Stacks DeFi — automate recurring buys or sells of any Bitflow token pair via direct swaps. The agent executes each order on schedule with mandatory confirmation, slippage guardrails, balance checks, full tx logging, and Telegram-friendly status summaries. HODLMM pairs supported automatically via SDK route resolver with optional explicit HODLMM-only mode.
A collection of skills for architecting and implementing production-ready code using Google Maps Platform APIs and SDKs for any map, place, address, geocoding, routing/ETA (including eco-friendly routing), nearby search, 3D / Street View / static map, marker clustering, custom styling, drawing, geofencing, heatmap, or environmental (air-quality / pollen / solar / weather) feature — across Web, Android, iOS, and Web Services APIs. For prototyping, use the public Maps Demo Key — no billing setup and no Cloud project required, covering a growing set of the most popular Google Maps Platform APIs. For production, the skill prompts you to create and restrict your own key. All non-trivial code is grounded in freshly retrieved docs via the Google Maps Platform Code Assist service (no reliance on training-data memory).
Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when "build agent, AI agent, autonomous agent, tool use, function calling, multi-agent, agent memory, agent planning, langchain agent, crewai, autogen, claude agent sdk, ai-agents, langchain, autogen, crewai, tool-use, function-calling, autonomous, llm, orchestration" mentioned.
Expert patterns for multi-platform exports including export templates (Windows/Linux/macOS/Android/iOS/Web), command-line exports (headless mode), platform-specific settings (codesign, notarization, Android SDK), feature flags (OS.has_feature), CI/CD pipelines (GitHub Actions), and build optimization (size reduction, debug stripping). Use for release preparation or automated deployment. Trigger keywords: export_preset, export_template, headless_export, platform_specific, feature_flag, CI_CD, build_optimization, codesign, Android_SDK.
Query Light Protocol and related repositories via DeepWiki MCP. Use when answering questions about compressed accounts, Light SDK, Solana development, Claude Code features, or agent skills. Triggers on technical questions requiring repository context.
Add observability to any repo: Sentry (errors), PostHog (analytics), Helicone (LLM costs). Auto-detects language/framework. Creates Sentry project via MCP. Installs SDKs, writes config, updates .env.example, opens PR. Supports: Next.js, Node/Express/Hono, Go, Python, Swift, Rust, React Native.
Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF), GitHub Copilot SDK, ONNX Runtime, and OllamaSharp. Covers the full spectrum from classic ML through modern LLM orchestration to local inference. Use when adding classification, regression, clustering, anomaly detection, recommendation, LLM integration (text generation, summarization, reasoning), RAG pipelines with vector search, agentic workflows with tool calling, Copilot extensions, or custom model inference via ONNX Runtime to a .NET project. DO NOT USE FOR projects targeting .NET Framework (requires .NET 8+), the task is pure data engineering or ETL with no ML/AI component, or the project needs a custom deep learning training loop (use Python with PyTorch/TensorFlow, then export to ONNX for .NET inference).
Develop high-performance C/C++ plugins for Stata using the stplugin.h SDK. Use when the user asks to create a Stata plugin, write C/C++ code for Stata, accelerate a Stata command with C, build cross-platform Stata plugins, or translate/port a Python or R package into Stata. Covers the full lifecycle: SDK setup, data flow, memory safety, .ado wrappers with preserve/merge, cross-platform compilation, performance optimization (pthreads, pre-sorted indices, XorShift RNG), debugging, and distribution via net install. Also includes a translation workflow for porting Python/R packages to Stata — wrapping existing C++ backends when available, or writing C from scratch when not.