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hrms-intelliforge
hrms-intelliforge contient 13 skills collectées depuis gengirish, avec une couverture métier par dépôt et des pages de détail sur le site.
Skills dans ce dépôt
Provides architecture knowledge for the IntelliForge HRMS platform. Use when exploring the codebase, adding features, debugging, or asking about project structure, tech stack, conventions, database schema, or design system.
Integrate AgentMail (agentmail.to) for AI-powered email — IntelliForge HRMS (TypeScript, shared HR inbox) and Interview Bot (Python, per-org inboxes, SMTP fallback). Use for invitations, notifications, webhooks, IMAP/SMTP/mobile clients, or attachments. Based on the official AgentMail skill (skills.sh/agentmail-to/agentmail-skills/agentmail).
Orchestrate LLM-powered interviews including prompt engineering, dynamic question generation, multi-model fallback, scoring rubrics, and code evaluation. Use when working with AI interview logic, OpenAI/Claude integration, scoring, or prompt templates.
Build and maintain the AI Interview Bot FastAPI backend with production best practices. Use when creating API endpoints, services, middleware, Pydantic schemas, or backend configuration.
Integrate Stripe subscription billing including checkout, webhooks, usage metering, plan enforcement, and customer portal. Use when working with payments, Stripe API, subscriptions, pricing tiers, or usage limits.
Set up and maintain PostgreSQL database, SQLAlchemy async models, Alembic migrations, multi-tenant queries, and Redis caching for the Interview Bot. Use when working with database schemas, migrations, ORM models, queries, or caching.
Configure Docker, Docker Compose, CI/CD pipelines, environment variables, and production deployments for the Interview Bot. Use when working with Dockerfiles, docker-compose, GitHub Actions, monitoring, or deployment configuration.
Type-safe form validation using React Hook Form v7 and Zod. Use when building forms with zodResolver, field arrays, multi-step wizards, or server-side validation in the Interview Bot frontend.
Build and maintain the Interview Bot Next.js frontend with dashboard UI, candidate interview pages, and responsive design. Use when creating pages, components, layouts, forms, or frontend configuration.
Handle real-time communication for text chat (WebSocket), voice interviews (LiveKit audio), and video interviews (LiveKit video). Use when working with WebSocket handlers, LiveKit integration, audio/video pipelines, or real-time interview features.
TanStack Query v5 data fetching patterns including useSuspenseQuery, useQuery, mutations, cache management, and API service integration. Use when fetching data, managing server state, or working with TanStack Query hooks in the Interview Bot frontend.
Write and run pytest backend tests and Playwright E2E tests for the Interview Bot. Use when creating tests, debugging test failures, adding test coverage, mocking external services, or configuring test infrastructure.
Zustand v4/v5 state management patterns for client-side stores. Use when creating stores, managing UI state, persisting data, or working with Zustand selectors in the Interview Bot frontend.