upgrade-python-deps
Upgrade Python dependencies using uv, then run post-upgrade checks to ensure nothing is broken.
Trouvez la capacité idéale pour votre agent.
Upgrade Python dependencies using uv, then run post-upgrade checks to ensure nothing is broken.
Setup Sentry Metrics in any project. Use this when asked to add Sentry metrics, track custom metrics, setup counters/gauges/distributions, or instrument application performance metrics. Supports JavaScript, TypeScript, Python, React, Next.js, and Node.js.
Setup Sentry Metrics in any project. Use this when asked to add Sentry metrics, track custom metrics, setup counters/gauges/distributions, or instrument application performance metrics. Supports JavaScript, TypeScript, Python, React, Next.js, and Node.js.
Setup Sentry Metrics in any project. Use this when asked to add Sentry metrics, track custom metrics, setup counters/gauges/distributions, or instrument application performance metrics. Supports JavaScript, TypeScript, Python, React, Next.js, and Node.js.
Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.
Generate optimized conference schedules using SolverForge (Timefold compatible). Use when the user needs to create conference schedules from CSV data with constraints like speaker conflicts, track distribution, room assignments, educational flow, and speaker availability. Supports both single-day and multi-day conferences. Python-native solution with no Java project setup required.
Find AILANG vs Python eval gaps and improve prompts/language. Use when user says 'find eval gaps', 'analyze benchmark failures', 'close Python-AILANG gap', or after running evals.
Run code snippets in 30+ programming languages including JavaScript, Python, TypeScript, Java, C, C++, Go, Rust, Ruby, PHP, and more. Use when the user wants to execute code, test algorithms, verify output, run scripts, or check code behavior. Supports both interpreted and compiled languages.
Guide for creating effective skills with UV + justfile structure. This skill should be used when users want to create a new skill (or update an existing skill) that extends the agent's capabilities with specialized knowledge, workflows, or tool integrations. Skills include PEP 723 compliant Python scripts managed via justfile for consistent execution.
Julia package equivalents for 137 K-Dense-AI scientific skills. Maps Python bioinformatics, chemistry, ML, quantum, and data science packages to native Julia ecosystem.
Generate production-ready project scaffolds for Grey Haven stack with Cloudflare Workers, React + TypeScript, Python + Pydantic, PlanetScale, proper structure, and configuration. Use when starting new projects, creating microservices, setting up monorepo workspaces, initializing projects, or when user mentions 'new project', 'project scaffold', 'project template', 'project setup', 'bootstrap project', 'project starter', or 'initialize project'.
Apply Grey Haven Studio's TypeScript/React and Python/FastAPI coding standards from production templates. Use when writing code, reviewing PRs, fixing linting errors, formatting files, or when the user mentions 'code standards', 'Grey Haven style', 'linting', 'Prettier', 'ESLint', 'Ruff', 'formatting rules', or 'coding conventions'. Includes exact Prettier/ESLint/Ruff configs, naming conventions, project structure, and multi-tenant database patterns.
Grey Haven's comprehensive testing strategy - Vitest unit/integration/e2e for TypeScript, pytest markers for Python, >80% coverage requirement, fixture patterns, and Doppler for test environments. Use when writing tests, setting up test infrastructure, running tests, debugging test failures, improving coverage, configuring CI/CD, or when user mentions 'test', 'testing', 'pytest', 'vitest', 'coverage', 'TDD', 'test-driven development', 'unit test', 'integration test', 'e2e', 'end-to-end', 'test fixtures', 'mocking', 'test setup', 'CI testing'.
Master TDD orchestration with multi-agent coordination, strict red-green-refactor enforcement, automated test generation, coverage tracking, and >90% coverage quality gates. Coordinates tdd-python, tdd-typescript, and test-generator agents. Use when implementing features with TDD workflow, coordinating multiple TDD agents, enforcing test-first development, or when user mentions 'TDD workflow', 'test-first', 'TDD orchestration', 'multi-agent TDD', 'test coverage', or 'red-green-refactor'.
Validate Python code quality with formatting, type checking, linting, and security analysis. Use for Python codebases to ensure PEP 8 compliance, type safety, and code quality.
Generate pytest-based unit tests for Python code. Creates test files following pytest conventions with proper fixtures, mocking, and parametrization.
Python Test-Driven Development expertise with pytest, strict red-green-refactor methodology, FastAPI testing patterns, and Pydantic model testing. Use when implementing Python features with TDD, writing pytest tests, testing FastAPI endpoints, developing with test-first approach, or when user mentions 'Python TDD', 'pytest', 'FastAPI testing', 'red-green-refactor', 'Python unit tests', 'test-driven Python', or 'Python test coverage'.
Identify memory leaks, inefficient allocations, and optimization opportunities in JavaScript/TypeScript and Python applications. Analyze heap snapshots, allocation patterns, garbage collection, and memory retention. Use when memory grows over time, high memory consumption detected, performance degradation, or when user mentions 'memory leak', 'memory usage', 'heap analysis', 'garbage collection', 'memory profiling', or 'out of memory'.