GitHub
finishing-development-branches
AI agent completes development branches with comprehensive quality gates, clean git history, and thorough PR preparation. Use when wrapping up features, preparing for merge, or finalizing PRs.
Skills IA Données et IA
Découvrez les skills Données et IA, comparez leurs dépôts et consultez leurs instructions.
Catégories: Données et IA
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Explorer
GitHub
evaluation-methodology
Methods for evaluating AI model outputs - exact match, semantic similarity, LLM-as-judge, comparative evaluation, ELO ranking. Use when measuring AI quality, building eval pipelines, or comparing models.
GitHub
ai-system-evaluation
End-to-end AI system evaluation - model selection, benchmarks, cost/latency analysis, build vs buy decisions. Use when selecting models, designing eval pipelines, or making architecture decisions.
GitHub
solving-problems
AI agent applies a 5-phase systematic framework for tackling complex problems when conventional approaches fail. Use when stuck, blocked, or troubleshooting issues.
GitHub
building-fastapi-apis
Builds high-performance FastAPI applications with async/await, Pydantic v2, dependency injection, and SQLAlchemy. Use when creating Python REST APIs, async backends, or microservices.
GitHub
developing-with-prisma
The agent implements Prisma ORM for type-safe database access with schema design, migrations, and queries. Use when building database layers, designing relational schemas, implementing type-safe queries, or man...
GitHub
managing-databases
AI agent performs database administration tasks including backup/restore, monitoring, replication, security hardening, and maintenance operations. Use when managing production databases, troubleshooting perform...
GitHub
service-discovery
Service discovery patterns with Consul, Kubernetes DNS, Eureka, health checks, and client-side load balancing.
GitHub
thinking-sequentially
AI agent structures complex reasoning through numbered thought sequences with explicit dependencies. Use when facing multi-step problems, complex debugging, or architectural decisions.
GitHub
monorepo-management
Enterprise monorepo patterns with Turborepo and Nx including task orchestration, caching, and CI/CD optimization
GitHub
building-responsive-layouts
Claude builds responsive web layouts with mobile-first CSS, fluid typography, and container queries. Use when creating adaptive UIs that work across all device sizes.
GitHub
mlops
MLOps practices including CI/CD for ML, experiment tracking, model monitoring, pipeline orchestration, and production ML operations.
GitHub
stacked-diffs-workflow
The agent implements stacked diffs (stacked PRs) for breaking large changes into reviewable chunks. Use when working on complex features, managing dependent changes, or optimizing code review flow.
GitHub
implementing-accessibility
Claude implements WCAG 2.1 AA compliant web interfaces with proper ARIA, keyboard navigation, and screen reader support. Use when building accessible components or auditing existing UIs.
GitHub
testingsecurity-testing
Security testing patterns covering OWASP Top 10, injection prevention, authentication, and vulnerability scanning
GitHub
service-mesh
Advanced service mesh implementation with Istio, Linkerd, traffic management, mTLS, and observability.
GitHub
data-engineering
ML data engineering covering data pipelines, data quality, collection strategies, storage, and versioning for machine learning systems.
GitHub
thinking-in-omega-modes
Applies 7 systematic thinking modes for breakthrough problem-solving and 10x improvements. Use when tackling complex problems, seeking transformative insights, or escaping conventional thinking traps.
GitHub
caching-strategies
Multi-layer caching with Redis, CDN, and browser caching for optimal application performance
GitHub
efficient-ai
Efficient AI techniques including model compression, quantization, pruning, knowledge distillation, and hardware-aware optimization for production systems.
GitHub
testingmutation-testing
Mutation testing with Stryker to verify test quality by introducing code mutations and measuring detection rates
GitHub
ml-systems
Machine Learning Systems - comprehensive knowledge for building production ML systems from data engineering through deployment and operations. Based on Harvard ML Systems course and Designing ML Systems by Chip...
GitHub
python
Python development with type hints, async patterns, testing, and modern best practices
GitHub
writing-plans
AI agent creates structured implementation plans with task breakdown, dependency mapping, risk assessment, and file-level detail. Use when planning features, projects, or complex implementations.
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.