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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
Uses power tools
Uses Bash, Write, or Edit tools
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Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Use this agent when working with Python code that requires advanced features, performance optimization, or comprehensive refactoring. Examples: <example>Context: User needs to optimize a slow Python function that processes large datasets. user: "This function is taking too long to process our data, can you help optimize it?" assistant: "I'll use the python-expert agent to analyze and optimize your Python code with advanced techniques and performance profiling."</example> <example>Context: User wants to implement async/await patterns in their existing synchronous Python code. user: "I need to convert this synchronous code to use async/await for better performance" assistant: "Let me use the python-expert agent to refactor your code with proper async/await patterns and concurrent programming techniques."</example> <example>Context: User needs help implementing complex Python design patterns. user: "I want to implement a factory pattern with decorators for my API endpoints" assistant: "I'll use the python-expert agent to implement advanced Python patterns with decorators and proper design principles."</example>
Python development ecosystem - uv, ruff, pytest, packaging, type checking
Research-backed best practices for building modern, production-grade Python packages — project structure, pyproject.toml, typing, testing, CI/CD, documentation, versioning, API design, packaging, security, and developer experience
Editorial "Python Pro" bundle for Claude Code from Antigravity Awesome Skills.
Python-specific validation, patterns, and expert agents
Profile API endpoints and run benchmarks to identify performance bottlenecks
Autonomous agent orchestrator for full development lifecycles with zero human input, session budget management, and crash recovery
Documentation review, cleanup, and generation with AI slop detection, style learning, and human-quality writing enforcement
Media generation capabilities for terminal recordings (VHS), browser recordings (Playwright), GIF processing, and media composition
Git and workspace operations for active development workflows - commit messages, PR prep, documentation updates, and version management
Project management plugin that aligns initiatives with GitHub data - turns repositories, issues, and projects into status dashboards
A plugin marketplace for Claude Code, Anthropic's agentic coding tool.
Night Market extends Claude Code with 23 plugins covering git workflows, code review, spec-driven development, architecture selection, codebase visualization, autonomous agents, multi-LLM delegation, ML-enhanced scoring, and multi-source research. 161 skills, 146 slash commands, and 50 agents. Each plugin installs independently.
Requires Claude Code 2.1.16+ and Python 3.9+ for hooks. See Requirements for details.
# Add the marketplace
/plugin marketplace add athola/claude-night-market
# Install plugins you need
/plugin install sanctum@claude-night-market # Git workflows
/plugin install pensive@claude-night-market # Code review
/plugin install spec-kit@claude-night-market # Spec-driven dev
# Use them
/prepare-pr # Prepare a pull request
/full-review # Run code review
Alternative: Install via npx with
npx skills add athola/claude-night-market (installs all plugins at once).
After installation, run claude --init for one-time setup.
Note: If the
Skilltool is unavailable, read skill files directly atplugins/{plugin}/skills/{skill-name}/SKILL.md.
# Install specific plugins
opkg i gh@athola/claude-night-market --plugins sanctum
opkg i gh@athola/claude-night-market --plugins pensive,conserve
# Plugins that depend on shared runtime skills (e.g. attune, conjure)
# automatically pull packages/core as a dependency
See the Installation Guide for detailed setup options.
23 plugins organized in four layers. Domain specialists depend on utility plugins, which depend on foundation plugins, which depend on the meta layer.
flowchart TB
classDef domainClass fill:#e8f4f8,stroke:#2980b9,stroke-width:2px,color:#2c3e50
classDef utilityClass fill:#f8f4e8,stroke:#f39c12,stroke-width:2px,color:#2c3e50
classDef foundationClass fill:#f4e8f8,stroke:#8e44ad,stroke-width:2px,color:#2c3e50
classDef metaClass fill:#e8f4e8,stroke:#27ae60,stroke-width:2px,color:#2c3e50
subgraph Domain["Domain Specialists"]
direction LR
D1[archetypes]:::domainClass
D2[pensive]:::domainClass
D3[parseltongue]:::domainClass
D4[memory-palace]:::domainClass
D5[spec-kit]:::domainClass
D6[minister]:::domainClass
D7[attune]:::domainClass
D8[scry]:::domainClass
D9[scribe]:::domainClass
D10[tome]:::domainClass
D11[gauntlet]:::domainClass
D12[cartograph]:::domainClass
end
subgraph Utility["Utility Layer"]
direction LR
U1[conserve]:::utilityClass
U2[conjure]:::utilityClass
U3[hookify]:::utilityClass
U4[egregore]:::utilityClass
U5[herald]:::utilityClass
U6[oracle]:::utilityClass
end
subgraph Foundation["Foundation Layer"]
direction LR
F1[imbue]:::foundationClass
F2[sanctum]:::foundationClass
F3[leyline]:::foundationClass
end
subgraph Meta["Meta Layer"]
direction LR
M1[abstract]:::metaClass
end
Domain ==> Utility ==> Foundation ==> Meta