Use when writing Go code that returns, wraps, or handles errors — choosing between sentinel errors, custom types, and fmt.Errorf (%w vs %v), structuring error flow, or deciding whether to log or return. Also use when propagating errors across package boundaries or using errors.Is/As, even if the user doesn't ask about error strategy. Does not cover panic/recover patterns (see go-defensive).
Use when declaring or initializing Go variables, constants, structs, or maps — including var vs :=, reducing scope with if-init, formatting composite literals, designing iota enums, and using any instead of interface{}. Also use when writing a new struct or const block, even if the user doesn't ask about declaration style. Does not cover naming conventions (see go-naming).
Use when writing concurrent Go code — goroutines, channels, mutexes, or thread-safety guarantees. Also use when parallelizing work, fixing data races, or protecting shared state, even if the user doesn't explicitly mention concurrency primitives. Does not cover context.Context patterns (see go-context).
Use when needing thread-safe primitives for performance-critical code. Covers Mutex (iOS 18+), OSAllocatedUnfairLock (iOS 16+), Atomic types, when to use locks vs actors, deadlock prevention with Swift Concurrency.
Configure Akka.NET with .NET Aspire for local development and production deployments. Covers actor system setup, clustering, persistence, Akka.Management integration, and Aspire orchestration patterns.
Create, update, refactor, explain, or review Semantic Kernel solutions using shared guidance plus language-specific references for .NET and Python.
Deploy Deepgram integrations to production environments. Use when deploying to cloud platforms, configuring containers, or setting up Deepgram in Docker/Kubernetes/serverless. Trigger: "deploy deepgram", "deepgram docker", "deepgram kubernetes", "deepgram production deploy", "deepgram cloud run", "deepgram lambda".
Create a new implementation plan file for new features, refactoring existing code or upgrading packages, design, architecture or infrastructure.
Local Microsoft Open Specifications corpus navigator for Windows protocols. Parses protocol message formats, looks up field definitions, maps data types, traces protocol state machines, and performs cross-reference analysis across related specifications. Use when the user asks protocol-level questions, needs message/structure details or wire-format field definitions, wants section-by-section summaries, needs to trace protocol state machines or sequencing rules, or requires cross-references across related MS-* specifications.
Implement robust error handling with user-friendly messages, specific exception types, fail-fast validation, centralized error boundaries, graceful degradation, and proper resource cleanup. Use this skill when writing try-catch blocks, raising exceptions, handling API errors, validating input, implementing error boundaries, managing external service failures, or ensuring resource cleanup. Apply when working with error handling code in any language, exception classes, error middleware, API error responses, retry logic, or any code that needs to handle failures gracefully while maintaining system stability and providing clear feedback to users.
Generate unit tests based on existing code patterns and testing frameworks.
Implements DeepAgent components using LangChain's deepagents SDK. Use when building deep agents with create_deep_agent, configuring backends/subagents/skills/memory, need DeepAgent patterns (sandbox, HITL interrupts, long-term memory, subagent spawning), or ask "implement deep agent", "add subagent", "configure backend".
Fix Node.js CLI tools crashing inside Docker containers when host-installed node_modules require a newer Node version than the container provides. Use when: (1) "SyntaxError: Invalid regular expression flags" with /v flag in string-width or similar packages, (2) node_modules installed on host with Node 20+ but container has Node 18, (3) `npm install` with file: protocol creates symlinks that break inside Docker, (4) pnpm workspace packages become broken symlinks in containers. Covers version detection, Node binary mounting, and npm install strategies for cross-version compatibility.
Step-by-step guide for adding a new agent framework adapter to Agent Kernel. Use this skill when you need to integrate a new agent framework (beyond OpenAI, CrewAI, LangGraph, Google ADK). Covers creating the adapter module, implementing Agent/Runner/Module subclasses, adding optional dependencies, exports, and tests.
This skill MUST be invoked when the user says "brownfield integration", "extend existing code", or "modify existing file". SHOULD also invoke when encountering tasks with `[EXTEND]` or `[MODIFY]` markers, implementing against existing codebases, or integrating with established interfaces.
Expert embedded systems engineer specializing in microcontroller programming, RTOS development, and hardware optimization. Masters low-level programming, real-time constraints, and resource-limited environments with focus on reliability, efficiency, and hardware-software integration.
Expert guidance for JAX (Just After eXecution) - high-performance numerical computing with automatic differentiation, JIT compilation, vectorization, and GPU/TPU acceleration; includes transformations (grad, jit, vmap, pmap), sharp bits, gotchas, and differences from NumPy
Split a TLA+ action into two sequential actions by introducing a new program counter (pc) state. Handles pc variable updates, UNCHANGED statements, TypeOk predicates, and follows naming conventions with renumbering. Use when the user asks to split, divide, or break an action into two parts, or wants to add an intermediate step to an action sequence.
Use when deploying code changes to dev environments (dev1-4), running terraform apply against dev, or verifying changes end-to-end. Triggers on "deploy to dev", "apply to dev2", "test in dev", "update dev environment".
Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with PyTorch/JAX/TensorFlow. For hardware-specific optimizations use qiskit (IBM) or cirq (Google); for open quantum systems use qutip.
Generate a high-level TLA+ model from source code (C, C++, Rust, etc.). Analyzes code to understand its purpose, creates abstractions, writes TLA+ specification, and proposes invariants and properties. Use when the user wants to model source code in TLA+, create a formal specification from implementation, or verify concurrent/distributed algorithms.
