AI & LLM

react-flow @existential-birds

React Flow (@xyflow/react) for workflow visualization with custom nodes and edges. Use when building graph...

react-flow-implementation @existential-birds

Implements React Flow node-based UIs correctly using @xyflow/react. Use when building flow charts, diagrams, visual...

react-flow-code-review @existential-birds

Reviews React Flow code for anti-patterns, performance issues, and best practices. Use when reviewing code that uses...

react-flow-architecture @existential-birds

Architectural guidance for building node-based UIs with React Flow. Use when designing flow-based applications,...

react-flow-advanced @existential-birds

Advanced React Flow patterns for complex use cases. Use when implementing sub-flows, custom connection lines,...

python-code-review @existential-birds

Reviews Python code for type safety, async patterns, error handling, and common mistakes. Use when reviewing .py...

pytest-code-review @existential-birds

Reviews pytest test code for async patterns, fixtures, parametrize, and mocking. Use when reviewing test_*.py files,...

pydantic-ai-tool-system @existential-birds

Register and implement PydanticAI tools with proper context handling, type annotations, and docstrings. Use when...

pydantic-ai-testing @existential-birds

Test PydanticAI agents using TestModel, FunctionModel, VCR cassettes, and inline snapshots. Use when writing unit...

pydantic-ai-model-integration @existential-birds

Configure LLM providers, use fallback models, handle streaming, and manage model settings in PydanticAI. Use when...

pydantic-ai-dependency-injection @existential-birds

Implement dependency injection in PydanticAI agents using RunContext and deps_type. Use when agents need database...

pydantic-ai-common-pitfalls @existential-birds

Avoid common mistakes and debug issues in PydanticAI agents. Use when encountering errors, unexpected behavior, or...

pydantic-ai-agent-creation @existential-birds

Create PydanticAI agents with type-safe dependencies, structured outputs, and proper configuration. Use when...

prometheus-go-code-review @existential-birds

Reviews Prometheus instrumentation in Go code for proper metric types, labels, and patterns. Use when reviewing code...

postgres-code-review @existential-birds

Reviews PostgreSQL code for indexing strategies, JSONB operations, connection pooling, and transaction safety. Use...

llm-judge @existential-birds

LLM-as-judge methodology for comparing code implementations across repositories. Scores implementations on...

llm-artifacts-detection @existential-birds

Detects common LLM coding agent artifacts in codebases. Identifies test quality issues, dead code, over-abstraction,...

langgraph-implementation @existential-birds

Implements stateful agent graphs using LangGraph. Use when building graphs, adding nodes/edges, defining state...

langgraph-code-review @existential-birds

Reviews LangGraph code for bugs, anti-patterns, and improvements. Use when reviewing code that uses StateGraph,...

langgraph-architecture @existential-birds

Guides architectural decisions for LangGraph applications. Use when deciding between LangGraph vs alternatives,...

howto-docs @existential-birds

How-To guide patterns for documentation - task-oriented guides for users with specific goals

healthkit-code-review @existential-birds

Reviews HealthKit code for authorization patterns, query usage, background delivery, and data type handling. Use...

go-testing-code-review @existential-birds

Reviews Go test code for proper table-driven tests, assertions, and coverage patterns. Use when reviewing *_test.go files.

go-code-review @existential-birds

Reviews Go code for idiomatic patterns, error handling, concurrency safety, and common mistakes. Use when reviewing...