vstorm-co/pydantic-deepagents

1

data-analysis Comprehensive data analysis skill for CSV files using Python and pandas

vstorm-co/pydantic-deepagents

25

2

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

vstorm-co/pydantic-deepagents

14

3

test-generator Generate pytest test cases for Python functions and classes

vstorm-co/pydantic-deepagents

14

4

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

vstorm-co/pydantic-deepagents

3

5

refactor Refactor code to improve structure and maintainability

vstorm-co/pydantic-deepagents

2

6

report-writing Guidelines for writing well-structured, cited research reports

vstorm-co/pydantic-deepagents

2

7

skill-creator Create new reusable skills from conversation context

vstorm-co/pydantic-deepagents

2

8

systematic-debugging Systematic approach to diagnosing and fixing errors

vstorm-co/pydantic-deepagents

2

9

build-and-compile Building, compiling, and resolving dependency issues across languages

vstorm-co/pydantic-deepagents

1

10

diagram-design Best practices for creating research diagrams with Excalidraw MCP tools

vstorm-co/pydantic-deepagents

1

11

environment-discovery Systematic exploration of unknown environments before starting work

vstorm-co/pydantic-deepagents

1

12

git-workflow Git operations: commits, branches, PRs, and conflict resolution

vstorm-co/pydantic-deepagents

1

13

performant-code Writing efficient code that handles large data and tight constraints

vstorm-co/pydantic-deepagents

1

14

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

vstorm-co/pydantic-deepagents

1

15

test-writer Generate comprehensive test suites for existing code

vstorm-co/pydantic-deepagents

1

16

verification-strategy Thorough verification of completed work before declaring done

vstorm-co/pydantic-deepagents

1