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Found 1,228 Skills
Deep Python code review of changed files using git diff analysis. Focuses on production quality, security vulnerabilities, performance bottlenecks, architectural issues, and subtle bugs in code changes. Analyzes correctness, efficiency, scalability, and production readiness of modifications. Use for pull request reviews, commit reviews, security audits of changes, and pre-deployment validation. Supports Django, Flask, FastAPI, pandas, and ML frameworks.
Invoke IMMEDIATELY via python script when user requests refactoring analysis, technical debt review, or code quality improvement. Do NOT explore first - the script orchestrates exploration.
Initialize a standardized Python project, including dependency management, code style checking, testing framework, version management, etc. This skill is triggered when users need to create a new Python project.
Analyze animated GIF files by extracting and viewing frames as sequential video. Use when: - User mentions a GIF file path (e.g., "./demo.gif", "~/Downloads/animation.gif") - User wants to analyze or understand a GIF animation - User asks about motion, changes, or content in a GIF - User attaches or references a .gif file for analysis - User wants to examine a screen recording in GIF format - User invokes /gif slash command Keywords: "GIF", ".gif", "animation", "animated", "frames", "screen recording", "analyze gif", "gif analysis", "view gif", "gif content", "gif motion" Trigger patterns: - Natural language: "Analyze this GIF: ./demo.gif" - Slash command: `/gif <path>` or `/gif <path> <message>` When triggered, extract frames using the Python script, view frames in order, and interpret as continuous video sequence.
Apply production-ready Databricks SDK patterns for Python and REST API. Use when implementing Databricks integrations, refactoring SDK usage, or establishing team coding standards for Databricks. Trigger with phrases like "databricks SDK patterns", "databricks best practices", "databricks code patterns", "idiomatic databricks".
Python testing mastery with pytest, fixtures, parametrize, mocking, and coverage. Use when user asks to "write tests", "add pytest fixtures", "mock a function", "parametrize tests", "run coverage", "debug failing test", "set up conftest", or any Python testing tasks.
Guidance for implementing proper asyncio task cancellation with signal handling in Python. This skill applies when implementing concurrent task runners that need graceful shutdown, handling KeyboardInterrupt/SIGINT in asyncio contexts, or managing task cleanup when using semaphores for concurrency limiting. Use when tasks involve asyncio.gather, CancelledError handling, or cleanup of tasks that haven't started execution.
Patterns for SQLite databases in Python projects - state management, caching, and async operations. Triggers on: sqlite, sqlite3, aiosqlite, local database, database schema, migration, wal mode.
Reverse engineer web APIs by capturing browser traffic (HAR files) and generating production-ready Python API clients. Use when the user wants to create an API client for a website, automate web interactions, or understand undocumented APIs. Activate on tasks mentioning "reverse engineer", "API client", "HAR file", "capture traffic", or "automate website".
Clean code patterns for Azure AI Search Python SDK (azure-search-documents). Use when building search applications, creating/managing indexes, implementing agentic retrieval with knowledge bases, or working with vector/hybrid search. Covers SearchClient, SearchIndexClient, SearchIndexerClient, and KnowledgeBaseRetrievalClient.
Use when building or structuring Python CLI commands with Typer, including commands, options, and multi-command apps.
Write Python docstrings following the Google Python Style Guide, using clear sections and examples.