Pytest Plugins

Enforce strict TDD cycles for features and bugfixes, create isolated git worktrees for safe development, generate detailed implementation plans broken into verifiable tasks, dispatch parallel subagents to execute plans or fix independent issues, perform technical code reviews on git diffs, investigate root causes systematically, and verify tests/builds before commits or PRs.

Manage Python projects via structured tracks for features, bugs, refactors: initialize context artifacts like product.md and tech-stack.md, create detailed specs and phased plans, implement tasks with strict TDD workflow using pytest coverage and git commits, monitor status, revert commits, and validate artifacts for consistency.

Automatically generate production-ready unit tests from source code files or snippets in JavaScript/TypeScript (using Jest, Vitest, or Mocha), Python (pytest), Java (JUnit 5), and Go. Auto-detects frameworks, covers happy paths, edge cases, boundaries, errors, and provides mocks for robust testing.

Build production-grade async Python backends and APIs with FastAPI and Django using expert guidance on architecture patterns, SQLAlchemy integration, pytest testing strategies, ruff optimization, and deployment best practices.

Automate full GitHub PR lifecycles using 260+ slash commands and agents that orchestrate multi-agent code reviews, generate/run tests, fix bugs/CI failures, manage branches, and drive autonomous merging with evidence validation in Claude Code.

Integrate Recursive Language Models into Claude Code to manage unbounded context across large codebases via REPL orchestration, sub-queries, model cascades, and multi-provider routing. Detect hallucinations with epistemic verification, benchmark performance, run pytest suites, review code changes for quality, and monitor sessions with hooks.

Delegate complex Python tasks to an expert agent that optimizes performance on large datasets via profiling, refactors synchronous code to async/await patterns, implements advanced design patterns with decorators and metaclasses, and ensures quality through pytest testing and mypy type checking.

Orchestrate full SDLC lifecycle phases from Inception through Transition using 58 AI agents and 170+ components to automate requirements, architecture evolution, testing orchestration, security gates, deployments, incident response, and project reporting via workflows, phase transitions, and quality checks.

Delegate complex Python tasks to a specialized expert agent for performance optimization via profiling, refactoring synchronous code to async/await patterns, implementing advanced design patterns with decorators and metaclasses, pytest testing, and mypy type checking.

Run autonomous full-stack dev workflows in Claude Code: generate PRDs/specs via interviews, execute Ralph/autodev loops for overnight PRD implementation with git branching/testing/committing, parallelize tasks across 12 agents (architect, frontend-dev, code-reviewer), build React/Tailwind/shadcn UIs and FastAPI backends, TDD/E2E test/verify/review code, automate git commits/PRs, and audit harness health.

Set up modern Python projects with uv for dependencies and environments, ruff for linting and formatting, ty for type checking, and pytest for testing. Migrate from pip or Poetry. Hooks check simdref availability on session start and enforce Node.js Flywheel security policies before Bash tool use.

Generate production-ready stateful CLI harnesses for GUI applications from local paths or GitHub repos, implementing Click CLI with REPL/JSON support, pytest unit/E2E tests, and docs. List installed harnesses, refine coverage gaps, run tests to verify functionality, and validate against standards.