pydantic-deepagents

Building, compiling, and resolving dependency issues across languages

Systematic code review for bugs, security, style, and performance

Working with diverse data formats: binary, text, structured, and custom

Systematic exploration of unknown environments before starting work

Git operations: commits, branches, PRs, and conflict resolution

Writing efficient code that handles large data and tight constraints

Refactor code to improve structure and maintainability

Create new reusable skills from conversation context

Systematic approach to diagnosing and fixing errors

Generate comprehensive test suites for existing code

Thorough verification of completed work before declaring done

Best practices for creating research diagrams with Excalidraw MCP tools

Guidelines for writing well-structured, cited research reports

Best practices for systematic research, source evaluation, and evidence gathering

Review Python code for quality, security, and best practices

Generate pytest test cases for Python functions and classes

Comprehensive data analysis skill for CSV files using Python and pandas