DebuggingInTears
Official@debuggingintears
Full-stack engineering expertise specializing in FastAPI backends, React frontend architecture, and high-performance database schema design.
Agent Skills by DebuggingInTears
Showing 24 vetted skills indexed across 1 GitHub repositories.
DebuggingInTearsui-ux-pro-max
Plan and implement UI/UX workflows for landing pages, dashboards, SaaS, and mobile apps.
DebuggingInTearspython-mcp-server-generator
Generate a typed Python MCP server scaffold with uv and FastMCP.
DebuggingInTearstailwind-theme-builder
Configures Tailwind v4 and shadcn/ui theming for React/Vite projects with dark mode and CSS variables.
DebuggingInTearspython-testing-patterns
Automate Python testing workflows with pytest, fixtures, and mocking patterns.
DebuggingInTearsprompt-engineering-patterns
Design structured prompts with chain-of-thought and few-shot patterns.
DebuggingInTearsdata-visualization
Generate accessible data visualizations with Python chart templates.
DebuggingInTearspython-type-safety
Enforce Python type annotations and strict mypy or pyright checks.
DebuggingInTearsshadcn
Manage shadcn/ui components across multi-repo projects via CLI workflows.
DebuggingInTearsrest-api-design
Design RESTful APIs with OpenAPI specs, HTTP methods, status codes, and versioning.
DebuggingInTearsdocker-expert
Optimize Docker images with multi-stage builds and security hardening.
DebuggingInTearsarchitecture-blueprint-generator
Generate architecture blueprint documents with diagrams from codebases.
DebuggingInTearsfastapi-templates
Generate FastAPI project skeletons with dependency injection and authentication scaffolding.
DebuggingInTearsfastapi
Implement FastAPI APIs with typed return models and dependency injection patterns.
DebuggingInTearsnextjs
Provide structured Next.js App Router patterns for routing, data fetching, and Vercel deployment.
DebuggingInTearsgraph-database-expert
Design and optimize graph schemas and traversals for SurrealDB knowledge graphs.
DebuggingInTearsredis-development
Optimize Redis deployments for performance, data modeling, and query patterns.
DebuggingInTearsneo4j-cypher-skill
Upgrade legacy Neo4j Cypher queries to modern 2025.x/2026.x syntax.
DebuggingInTearsvercel-react-best-practices
Analyze React/Next.js code for rendering, data fetching, and bundling optimizations.
DebuggingInTearspython-project-structure
Design Python project structures with module hierarchies and __all__ interfaces.
DebuggingInTearspydantic
Validate Python data against strict type specifications at runtime.
DebuggingInTearsfastapi-python
Build FastAPI backends with Pydantic v2 models and modular routing.
DebuggingInTearstailwind-design-system
Develop scalable Tailwind v4 design systems with design tokens and CVA variants.
DebuggingInTearsdataverse-python-quickstart
Automate Dataverse Python SDK setup and CRUD workflows.
DebuggingInTearsnext-best-practices
Standardize Next.js development with official best practices for file conventions and data patterns.
Frequently Asked Questions About DebuggingInTears
FAQPage SchemaWhat specific technical tasks can I perform using these skills?▼
You can generate structured FastAPI project skeletons, implement strict Pydantic v2 data validation, configure Tailwind v4 design systems, and optimize graph database schemas for SurrealDB or Neo4j. These capabilities support end-to-end development from backend routing to frontend component theming.
Which engineering personas benefit most from these capabilities?▼
Full-stack developers, backend engineers, and frontend architects benefit from these standardized patterns. The skills are designed for professionals building scalable SaaS platforms who require consistent project structures, type-safe interfaces, and optimized rendering patterns for React and Next.js environments.
What are the primary prerequisites for implementing these patterns?▼
Implementation requires a foundational environment configured for modern web development, specifically Node.js for React/Next.js projects and a standard runtime for FastAPI. Users should have existing knowledge of component-based architecture and relational or graph database modeling to effectively apply these structural templates.