By athola
Profile Python performance bottlenecks with cProfile/py-spy, analyze pytest test suites for quality/coverage, check async code for issues/patterns, lint/fix with ruff, optimize algorithms/memory, generate unit/integration tests, and package/publish projects using uv/pyproject.toml.
npx claudepluginhub athola/claude-night-market --plugin parseltongueAnalyzes Python test suites for quality, coverage, and improvement opportunities.
Analyzes Python async code for correctness, patterns, and potential issues.
Profiles Python code for performance bottlenecks using cProfile, memory_profiler, or py-spy.
Enforce strict ruff rules without per-file-ignores bypasses. Use for lint errors or code quality reviews.
Python profiling, bottleneck identification, and algorithm optimization. Use when code is slow.
Python 3.9+ expert (uv, ruff, pydantic, FastAPI). Use PROACTIVELY for Python development or optimization.
Expert Python testing agent specializing in pytest, TDD workflows, mocking strategies, and thorough test coverage.
Async Python patterns and concurrency: async APIs, I/O-bound apps, rate limiting, context managers
Python package creation and distribution: pyproject.toml, entry points, PyPI publishing, CI/CD
Python performance profiling and optimization: bottleneck detection, memory tuning, benchmarking
Python testing patterns: pytest setup, fixtures, TDD, mocking, async tests, and integration tests
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
Uses power tools
Uses Bash, Write, or Edit tools
Comprehensive PR review agents specializing in comments, tests, error handling, type design, code quality, and code simplification
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Orchestrate multi-agent teams for parallel code review, hypothesis-driven debugging, and coordinated feature development using Claude Code's Agent Teams
Comprehensive startup business analysis with market sizing (TAM/SAM/SOM), financial modeling, team planning, and strategic research