Rechercher

PythonReactSEOPDF

Skills IA Bases de données

Découvrez les skills Bases de données, comparez leurs dépôts et consultez leurs instructions.

Catégories: Bases de données

12,073–12,096 sur 85,283

Bases de données Effacer les filtres

Explorer

GitHub

backend-architecture-enforcer

yonatangross

Enforces FastAPI Clean Architecture with blocking validation. Use when implementing router-service-repository patterns, enforcing layer separation, or validating dependency injection in backend code.

GitHub

rate-limiting

yonatangross

API rate limiting with token bucket, sliding window, and Redis distributed patterns. Use when implementing rate limits, throttling requests, handling 429 Too Many Requests, protecting against API abuse, or conf...

GitHub

strawberry-graphql

yonatangross

Strawberry GraphQL library for Python with FastAPI integration, type-safe resolvers, DataLoader patterns, and subscriptions. Use when building GraphQL APIs with Python, implementing real-time features, or creat...

GitHub

golden-dataset-validation

yonatangross

Use when validating golden dataset quality. Runs schema checks, duplicate detection, and coverage analysis to ensure dataset integrity for AI evaluation.

GitHub

golden-dataset-management

yonatangross

Use when backing up, restoring, or validating golden datasets. Prevents data loss and ensures test data integrity for AI/ML evaluation systems.

GitHub

rnow-train-jsonl

ReinforceNow

Format train.jsonl training data for ReinforceNow. Use when creating train.jsonl, formatting training entries, using tools/rewards per entry, or setting up sandbox/docker. Triggers on "train.jsonl", "training d...

GitHub

rnow-cli

ReinforceNow

Use the ReinforceNow CLI for RLHF training. Use when running rnow commands, initializing projects, submitting training runs, testing rollouts, or downloading models. Triggers on "rnow", "rnow init", "rnow run",...

GitHub

fine-tuning-customization

yonatangross

LLM fine-tuning with LoRA, QLoRA, DPO alignment, and synthetic data generation. Efficient training, preference learning, data creation. Use when customizing models for specific domains.

GitHub

ollama-local

yonatangross

Local LLM inference with Ollama. Use when setting up local models for development, CI pipelines, or cost reduction. Covers model selection, LangChain integration, and performance tuning.

GitHub

wcag-compliance

yonatangross

WCAG 2.2 AA accessibility compliance patterns for web applications. Use when auditing accessibility or implementing WCAG requirements.

GitHub

doctor

yonatangross

SkillForge health diagnostics command that validates plugin configuration and reports issues. Use when running doctor checks or troubleshooting plugin health.

GitHub

stacked-prs

yonatangross

Multi-PR development for large features. Stack dependent PRs, manage rebases, and get faster reviews on smaller changes. Use when creating stacked PRs.

GitHub

git-recovery

yonatangross

Quick recovery from common git mistakes including undo commits, recover branches, and reflog operations. Use when you need to undo, recover, or fix Git history.

GitHub

worktree-coordination

yonatangross

Manage multiple Claude Code instances across git worktrees. Check status, claim/release file locks, sync decisions, and prevent conflicts. Use when coordinating multiple worktrees or Claude instances.

GitHub

devops-deployment

yonatangross

Use when setting up CI/CD pipelines, containerizing applications, deploying to Kubernetes, or writing infrastructure as code. DevOps & Deployment covers GitHub Actions, Docker, Helm, and Terraform patterns.

GitHub

observability-monitoring

yonatangross

Use when adding logging, metrics, tracing, or alerting to applications. Observability & Monitoring covers structured logging, Prometheus metrics, OpenTelemetry tracing, and alerting strategies.

GitHub

webapp-testing

yonatangross

Use when testing web applications with AI-assisted Playwright. Webapp testing covers autonomous test agents for planning, generating, and self-healing tests.

GitHub

llm-testing

yonatangross

Testing patterns for LLM-based applications. Use when testing AI/ML integrations, mocking LLM responses, testing async timeouts, or validating structured outputs from LLMs.

GitHub

msw-mocking

yonatangross

Mock Service Worker (MSW) 2.x for API mocking. Use when testing frontend components with network mocking, simulating API errors, or creating deterministic API responses in tests.

GitHub

vcr-http-recording

yonatangross

VCR.py HTTP recording for Python tests. Use when testing Python code making HTTP requests, recording API responses for replay, or creating deterministic tests for external services.

GitHub

property-based-testing

yonatangross

Property-based testing with Hypothesis for discovering edge cases automatically. Use when testing invariants, finding boundary conditions, implementing stateful testing, or validating data transformations.

GitHub

test-data-management

yonatangross

Test data management with fixtures and factories. Use when creating test data strategies, implementing data factories, managing fixtures, or seeding test databases.

GitHub

pytest-advanced

yonatangross

Advanced pytest patterns including custom markers, plugins, hooks, parallel execution, and pytest-xdist. Use when implementing custom test infrastructure, optimizing test execution, or building reusable test ut...

GitHub

unit-testing

yonatangross

Unit testing patterns and best practices. Use when writing isolated unit tests, implementing AAA pattern, designing test isolation, or setting coverage targets for business logic.

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.

Plus de filtres

Popularité

Tags populaires