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database-seed
Create robust, error-proof Prisma seed scripts with comprehensive error handling and validation.
Skills IA Entreprise
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Catégories: Entreprise
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GitHub
code-review
Review code for quality, security, performance, and best practices. Use when reviewing changes before commit, auditing code for issues, or suggesting improvements.
GitHub
debugging
Debug code errors systematically. Use when analyzing error messages, fixing bugs, resolving build/lint errors, or troubleshooting runtime issues.
GitHub
argentic-framework-development
Expert knowledge for building AI agents with Argentic - a Python microframework for async MQTT-based agents with multi-LLM support, custom tools, and multi-agent orchestration
GitHub
atomic-blocks
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...
GitHub
meta-self
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 work...
GitHub
llm4s-scala
LLM4S Scala functional LLM interfaces with Effect system integration. Use when building LLM applications in Scala with ZIO or Cats Effect, implementing type-safe AI pipelines with functional error handling, cre...
GitHub
lmql-constraints
LMQL constraint-guided generation DSL for type-safe prompting with grammar constraints and logical conditions. Use when building structured LLM outputs with guaranteed format compliance, implementing constraine...
GitHub
mcp-categorical
MCP (Model Context Protocol) server patterns with categorical tool composition and typed context protocols. Use when building MCP servers with categorical composition patterns, designing tool interfaces using f...
GitHub
categorical-meta-prompting
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. In...
GitHub
categorical-structure-builder
Universal template for implementing categorical structures in meta-prompting frameworks. Applies to functors, monads, comonads, natural transformations, adjunctions, hom-equivalences, limits, colimits, and enri...
GitHub
recursive-meta-prompting
Recursive Meta-Prompting (RMP) implementation with unified categorical syntax. Supports @mode:iterative, @quality: thresholds, >=> Kleisli composition, and comonadic context extraction. Use when implementing it...
GitHub
dynamic-prompt-registry
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...
GitHub
prompt-dsl
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...
GitHub
dspy-categorical
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...
GitHub
effect-ts-ai
@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...
GitHub
cc2-research-framework
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...
GitHub
guidance-grammars
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...
GitHub
langgraph-orchestration
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...
GitHub
categorical-property-testing
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...
GitHub
arxiv-categorical-ai
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...
GitHub
discopy-nlp
DisCoPy categorical quantum NLP for string diagrams, monoidal categories, and compositional semantics in Python. Use when implementing compositional distributional semantics, building string diagram computation...
GitHub
hasktorch-typed
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...
GitHub
voltagent-multiagent
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...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.