Foundational Go patterns covering types, interfaces, goroutines, channels, and common idioms. Use when writing Go code, understanding Go's concurrency model, or needing guidance on which specialized Go skill to use. This is the entry point for Go development.
Go 1.23+ development specialist covering Chi, GORM, and concurrent programming patterns. Use when building high-performance microservices, CLI tools, or cloud-native applications.
Foundational Java patterns covering core syntax, object-oriented programming, generics, collections, streams, lambdas, and modern Java features. Use when writing Java code, understanding the type system, working with collections/streams, or needing guidance on which specialized Java skill to use. This is the entry point for Java development.
Kotlin-specific library development patterns. Use when creating Kotlin libraries, designing idiomatic Kotlin APIs with extension functions and DSLs, configuring Gradle Kotlin DSL (build.gradle.kts), managing multiplatform projects, testing with Kotest/JUnit, writing KDoc documentation, or publishing to Maven Central. Extends meta-library-dev with Kotlin tooling and ecosystem practices.
Foundational Objective-C patterns covering classes, protocols, categories, memory management (ARC/retain-release), blocks, GCD, and Foundation framework. Use when writing Objective-C code, working with Cocoa/Cocoa Touch APIs, bridging to Swift, or needing guidance on Apple platform development patterns. This is the entry point for Objective-C development.
Foundational Python patterns covering core syntax, idioms, type hints, testing, and modern tooling. Use when writing Python code, understanding Pythonic patterns, working with type hints, or needing guidance on which specialized Python skill to use. This is the entry point for Python development.
Foundational Roc patterns covering platform/application architecture, records, tags, pattern matching, abilities, and functional idioms. Use when writing Roc code, understanding the platform model, or needing guidance on which specialized Roc skill to use. This is the entry point for Roc development.
Foundational Rust patterns covering core syntax, traits, generics, lifetimes, and common idioms. Use when writing Rust code, understanding ownership basics, working with Option/Result, or needing guidance on which specialized Rust skill to use. This is the entry point for Rust development.
Rust 1.92+ development specialist covering Axum, Tokio, SQLx, and memory-safe systems programming. Use when building high-performance, memory-safe applications or WebAssembly.
Foundational Scala patterns covering immutability, pattern matching, traits, case classes, for-comprehensions, and functional programming. Use when writing Scala code, understanding the type system, or needing guidance on which specialized Scala skill to use. This is the entry point for Scala development.
Foundational TypeScript patterns covering types, interfaces, generics, utility types, and common idioms. Use when writing TypeScript code, understanding the type system, or needing guidance on which specialized TypeScript skill to use. This is the entry point for TypeScript development.
Comprehensive guide for building production-grade LLM applications using LangChain's chains, agents, memory systems, RAG patterns, and advanced orchestration
Model Context Protocol (MCP) server implementation patterns with LangChain4j. Use when building MCP servers to extend AI capabilities with custom tools, resources, and prompt templates.
LangChain.js - TypeScript framework for building LLM-powered applications with agents, chains, RAG, tools, memory, and integrations for OpenAI, Anthropic, Google, and hundreds of other providers
Replaces Phoenix observability with Langfuse Cloud (EU) traceability for pharmaceutical test generation. Adds @observe decorators to existing code, configures LlamaIndex callbacks, propagates GAMP-5 compliance attributes, and removes Phoenix dependencies. Use PROACTIVELY when implementing Task 2.3 (LangFuse setup), migrating observability systems, or ensuring ALCOA+ trace attribution. MUST BE USED for pharmaceutical compliance monitoring requiring persistent cloud storage.
Use when specifying or implementing LangGraph applications - from architecture planning and specification writing to actual code implementation. Also use for designing agent workflows or learning LangGraph patterns. This is a comprehensive guide for building AI agents with LangGraph, covering core concepts, architecture patterns, memory management, tool integration, and advanced features.
Architect-level development, audit, and migration of multi-agent systems using LangGraph (v1+) and LangChain (v1+). Use when building or refactoring supervisor/subagent architectures, orchestrator-worker workflows, routing/hand-offs, agentic RAG, memory (short + long-term), state + context engineering, guardrails + human-in-the-loop, MCP tool integration, observability (LangSmith/OpenTelemetry), deployment, and performance/cost optimization — or when migrating off deprecated patterns like `langgraph.prebuilt.create_react_agent` and libraries like `langgraph-supervisor(-py)`, LlamaIndex agents, CrewAI, Agno, or OpenAI Agents.
Validates LangGraph implementations for correctness, consistency, and integration readiness. Use this skill when implementing, reviewing, or debugging any LangGraph code - agents, nodes, subgraphs, state schemas, or graph compositions. Prevents common LangGraph failures including orphaned nodes, state key mismatches, broken conditional edges, and integration incompatibilities. Triggers on LangGraph development tasks, code reviews, or when debugging graph execution issues.
LangSmith Agent Builder - No-code platform for creating AI agents with built-in tools (Gmail, Slack, GitHub, Linear), OAuth integrations, MCP server support, Slack deployment, and programmatic invocation via LangGraph SDK
LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.
Use for language design questions including syntax decisions, semantics, grammar authoring, and comparing DomainLang with other DSLs. Activate when designing new language features, evaluating syntax alternatives, or discussing DDD pattern representation.
Guidelines and workflow for working on Laravel 11 or Laravel 12 applications across common stacks (API-only or full-stack), including optional Docker Compose/Sail, Inertia + React, Livewire, Vue, Blade, Tailwind v4, Fortify, Wayfinder, PHPUnit, Pint, and Laravel Boost MCP tools. Use when implementing features, fixing bugs, or making UI/backend changes while following project-specific instructions (AGENTS.md, docs/).
Design Laravel app architecture with services, repositories, actions, and clean code patterns. Use when structuring projects, creating services, implementing DI, or organizing code layers.
Use when implementing user authentication, API tokens, social login, or authorization. Covers Sanctum, Passport, Socialite, Fortify, policies, and gates for Laravel 12.
Integrate Stripe and Paddle payments with Laravel Cashier. Use when implementing subscriptions, invoices, payment methods, webhooks, or billing portals.
Laravel Dusk - Browser automation and testing API for Laravel applications. Use when writing browser tests, automating UI testing, testing JavaScript interactions, or implementing end-to-end tests in Laravel.
Multi-tenant application architecture patterns. Use when working with multi-tenant systems, tenant isolation, or when user mentions multi-tenancy, tenants, tenant scoping, tenant isolation, multi-tenant.
Code quality tooling with PHPStan, Pint, and strict types. Use when working with code quality, static analysis, formatting, or when user mentions PHPStan, Pint, quality, static analysis, type safety, code style, linting.
Test-Driven Development specifically for Laravel applications using Pest PHP. Use when implementing any Laravel feature or bugfix - write the test first, watch it fail, write minimal code to pass.
Provides strategies for efficiently transforming large text files (thousands to millions of lines) using text editors like Vim, sed, or awk. This skill should be used when tasks involve bulk text transformations, CSV manipulation at scale, pattern-based edits across massive files, or when keystroke/operation efficiency is constrained. Applicable to tasks requiring macros, regex substitutions, or batch processing of structured text data.
Compiles LaTeX source code to PDF using pdflatex. Use this skill whenever the user asks to create and compile LaTeX documents, generate PDFs from LaTeX, or compile existing LaTeX code in artifacts.
Search and navigate The Fold's skill lattice using meta-tooling. Use for finding functions, exploring dependencies, type-aware queries, and cross-reference analysis. Invoke when searching for capabilities, exploring the codebase structure, or finding how functions relate.