Browse published AI skills maintained by manutej. Compare skill descriptions and follow each source repository for setup instructions.
Indexed skills
99Repository stars across indexed skills
2,766Repository forks
527Average repository stars per indexed skill
28Repository stars may repeat across skills from the same repository.
Universal template for implementing categorical structures in meta-prompting frameworks. Applies to functors, monads, comonads, natural transformations, adjunctions, hom-equivalences, limits, colimits, and enri...
Recursive Meta-Prompting (RMP) implementation with unified categorical syntax. Supports @mode:iterative, @quality: thresholds, >=> Kleisli composition, and comonadic context extraction. Use when implementing it...
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 referencin...
Domain-specific language for categorical prompt composition with functor combinators and natural transformation operators. Use when building composable prompt templates, implementing typed prompt algebras, crea...
DSPy compositional prompt optimization with categorical signatures, module chaining, and automated prompt tuning. Use when building declarative LLM programs with typed signatures, composing multi-step reasoning...
@effect/ai integration patterns for categorical AI composition, typed error handling, and production prompt pipelines. Use when building AI applications with Effect-TS, composing LLM calls with typed errors, cr...
CC2.0 seven-function research workflow (observe, reason, create, orchestrate, learn, verify, deploy) for categorical AI research. Use when conducting systematic research on categorical AI topics, coordinating m...
Guidance library grammar-constrained generation with categorical structure. Use when implementing structured LLM outputs with grammar constraints, building template-based generation with guaranteed formats, cre...
LangGraph stateful multi-agent graphs with categorical coordination patterns and cyclic workflows. Use when building stateful AI agent systems, implementing multi-agent orchestration with conditional routing, c...
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 cod...
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 researc...
DisCoPy categorical quantum NLP for string diagrams, monoidal categories, and compositional semantics in Python. Use when implementing compositional distributional semantics, building string diagram computation...
Hasktorch type-safe tensor operations with categorical structure preservation. Use when implementing type-safe deep learning in Haskell, leveraging dependent types for tensor shape verification, applying catego...
VoltAgent multi-agent system design with natural transformation coordination between agents. Use when building TypeScript multi-agent AI systems, implementing agent coordination with categorical patterns, desig...
Systematic prompt evaluation framework with MATH, GSM8K, and Game of 24 benchmarks. Use when evaluating prompt effectiveness on standard benchmarks, comparing meta-prompting strategies quantitatively, measuring...
[0,1]-enriched category implementation for gradient-based prompt quality optimization. Use when implementing quality-aware prompt systems, building enriched categorical structures for prompt evaluation, creatin...
Spivak-Niu polynomial functor implementations for learner composition and dynamical systems. Use when modeling learning systems as categorical structures, composing machine learning components with polynomial f...
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),...
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 syst...
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 fu...
Expert guidance for researching, documenting, and integrating Model Context Protocol (MCP) servers and tools. Covers MCP architecture, server/client implementation patterns, tool discovery, integration workflow...
Expert-level category theory knowledge for rigorous mathematical reasoning. Use when working with categorical structures, functors, natural transformations, adjunctions, limits, toposes, monoidal categories, en...
Comprehensive Supabase integration covering authentication, database operations, realtime subscriptions, storage, and MCP server patterns for building production-ready backends with PostgreSQL, Auth, and real-t...
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 writin...
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.