manutej

Expert integration patterns for Claude API and TypeScript SDK covering Messages API, streaming responses, tool use, error handling, token optimization, and production-ready implementations for building AI-powered applications

Comprehensive guide for building production-grade LLM applications using LangChain's chains, agents, memory systems, RAG patterns, and advanced orchestration

Complete guide for Axum web framework including routing, extractors, middleware, state management, error handling, and production deployment

Complete guide for building scalable microservices with Express.js including middleware patterns, routing strategies, error handling, production architecture, and deployment best practices

Comprehensive Express.js development skill covering routing, middleware, request/response handling, error handling, and building production-ready REST APIs

Modern Python API development with FastAPI covering async patterns, Pydantic validation, dependency injection, and production deployment

Comprehensive guide for building production-ready microservices with FastAPI including REST API patterns, async operations, dependency injection, and deployment strategies

Comprehensive FastAPI skill for building modern Python web APIs with focus on customer support systems, ticket management, real-time chat, and backend operations

Composable atomic blocks for categorical meta-prompting. Defines 16 reusable blocks across 4 layers (Assessment, Transformation, Refinement, Composition) that can be composed to build custom workflows. Enables progressive disclosure: simple commands work unchanged, power users can override individual blocks or compose freely.

Master reference for categorical meta-prompting unified syntax. Contains all modifiers, operators, composition patterns, and execution protocols. Use this skill for self-reference when executing any prompt workflow, ensuring consistent syntax across all commands and skills.

Dynamic prompt registry with unified categorical syntax. Supports @skills:discover(), @skills:compose(A⊗B), Reader monad for runtime lookup, and quality-tracked prompt libraries. Use for meta-prompts referencing sub-prompts, building prompt libraries, implementing deferred resolution, or composing templates dynamically.

Universal template for implementing categorical structures in meta-prompting frameworks. Applies to functors, monads, comonads, natural transformations, adjunctions, hom-equivalences, limits, colimits, and enriched categories. Use when extending frameworks with new categorical constructs.

Recursive Meta-Prompting (RMP) implementation with unified categorical syntax. Supports @mode:iterative, @quality: thresholds, >=> Kleisli composition, and comonadic context extraction. Use when implementing iterative prompt improvement, quality-gated generation loops, or applying categorical fixed-point semantics with convergence guarantees.

Full categorical framework for meta-prompting with verified laws. Use when implementing functor-based task routing, monadic iterative refinement, comonadic context extraction, or quality-tracked composition. Integrates F (Functor), M (Monad), W (Comonad), and [0,1]-enriched quality categories.

Systematic analysis patterns for categorical AI papers (Gavranović, de Wynter, Bradley, Zhang). Use when analyzing academic papers on categorical deep learning, extracting categorical structures from AI research, mapping meta-prompting concepts to category theory, or building comprehensive literature reviews on categorical approaches to AI.

Property-based testing for functor laws, monad laws, and naturality conditions using fp-ts and fast-check. Use when validating categorical implementations in TypeScript, testing algebraic laws in functional code, verifying functor/monad/applicative instances, or building test suites for categorical abstractions.

Comprehensive API gateway patterns skill covering Kong, routing, rate limiting, authentication, load balancing, traffic management, and production gateway architecture

Comprehensive guide for building production-ready microservices with FastAPI including REST API patterns, async operations, dependency injection, and deployment strategies

Comprehensive FastAPI skill for building modern Python web APIs with focus on customer support systems, ticket management, real-time chat, and backend operations

Complete guide for Go backend development including concurrency patterns, web servers, database integration, microservices, and production deployment

Comprehensive React component testing with Jest and React Testing Library covering configuration, mocking strategies, async testing patterns, hooks testing, and integration testing best practices

Expert guidance for researching, documenting, and integrating Model Context Protocol (MCP) servers and tools. Covers MCP architecture, server/client implementation patterns, tool discovery, integration workflows, security best practices, and multi-language SDK usage (Python, TypeScript, C#, Java, Rust). Enables seamless integration of MCP tools into Claude Code and AI applications.

Expert MCP (Model Context Protocol) orchestration with n8n workflow automation. Master bidirectional MCP integration, expose n8n workflows as AI agent tools, consume MCP servers in workflows, build agentic systems, orchestrate multi-agent workflows, and create production-ready AI-powered automation pipelines with Claude Code integration.

Comprehensive guide for designing RESTful APIs including resource modeling, versioning strategies, HATEOAS, pagination, filtering, and HTTP best practices

Container orchestration with Docker Compose for multi-container applications, networking, volumes, and production deployment

Comprehensive Express.js development skill covering routing, middleware, request/response handling, error handling, and building production-ready REST APIs

Modern Python API development with FastAPI covering async patterns, Pydantic validation, dependency injection, and production deployment

Comprehensive guide for building GraphQL APIs including schema design, queries, mutations, subscriptions, resolvers, type system, error handling, authentication, authorization, caching strategies, and production best practices

Comprehensive Node.js development skill covering event loop, async patterns, streams, file system, HTTP servers, process management, and modern Node.js best practices

Comprehensive Elm functional programming for web development including The Elm Architecture, type system, JavaScript interop, and production-ready patterns

Master the Purify library for practical functional programming in TypeScript with algebraic data types (Maybe, Either, EitherAsync, MaybeAsync), composable error handling, data transformations, Codec for runtime type safety, List operations, Tuple utilities, and functional patterns. Use when working with Purify's Maybe/Either types, async error handling with EitherAsync/MaybeAsync, runtime validation with Codecs, or building practical functional TypeScript applications with cleaner syntax than fp-ts.

Comprehensive F* proof-oriented programming for formal verification including dependent types, refinement types, effect system, SMT solver integration, tactic-based interactive theorem proving, and verified code extraction to OCaml, F#, C, WebAssembly, and Assembly

Master the fp-ts library for typed functional programming in TypeScript, including Option, Either, Task, TaskEither, Reader, State, IO, Array, Record, pipe/flow composition, Do notation, optics (lenses/prisms), and integration with the Effect-TS ecosystem. Use when working with fp-ts data types, composing functional pipelines, handling effects functionally, implementing monadic patterns, or using fp-ts utilities for type-safe functional code.

Master functional programming principles and patterns including purity, immutability, composition, higher-order functions, algebraic data types, functors, monads, and effect management. Use when working with functional paradigms, pure functions, immutable data structures, function composition, type-safe error handling, or implementing functional patterns like map/filter/reduce, currying, partial application, recursion, lazy evaluation, or referential transparency.

Master functional programming in TypeScript with type-safe patterns, strict typing, advanced type system features, discriminated unions, mapped types, conditional types, and functional patterns. Use when writing TypeScript code with functional paradigms, type-safe error handling with Option/Either types, implementing type-safe composition, leveraging TypeScript's type system for functional patterns, or ensuring compile-time safety in functional code.

Expert-level category theory knowledge for rigorous mathematical reasoning. Use when working with categorical structures, functors, natural transformations, adjunctions, limits, toposes, monoidal categories, enriched categories, higher categories, operads, or any formal categorical construction. Ideal for proofs, diagram chases, universal properties, coherence conditions, and foundational mathematical abstractions.

Category theory for compositional computing with string diagrams, quantum circuits, and QNLP. Covers monoidal categories, functors, tensor evaluation, and practical applications in quantum natural language processing and diagrammatic reasoning.

Use when generating WOW-level animated components for course pages, dashboards, hero sections, product landing pages, or technical demos. Triggers on 'animated component', 'make this WOW', 'add animation', 'magnetic button', 'number ticker / number flow', 'bento grid', 'hero text reveal', 'hero parallax', 'sticky scroll', 'animated beam', 'dynamic island', '3D tilt card', 'border beam', 'shadcn animations', 'smoothui style', 'aceternity style', 'magic UI', 'motion primitives', 'react bits', 'animate UI', 'cult UI', 'animated dashboard widget', 'scroll storytelling', 'KPI counter', 'animated background', 'interactive experience'. Also use when extending the codebase-to-course design system with motion, building interactive course tutorials beyond single-page HTML, or producing dashboard widgets with data-viz motion. Hybrid shadcn structure + smoothui motion vocabulary.

Recursive Meta-Prompting (RMP) implementation patterns with monadic refinement loops, quality convergence, and self-improvement. Use when implementing iterative prompt improvement systems, building self-refining AI pipelines, creating quality-gated generation loops, or applying categorical fixed-point semantics to prompt engineering with convergence guarantees.