Vstorm

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

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Refactor code to improve structure and maintainability

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Generate comprehensive test suites for existing code

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

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Building, compiling, and resolving dependency issues across languages

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Review Python code for quality, security, and best practices

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Generate pytest test cases for Python functions and classes

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

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Systematic exploration of unknown environments before starting work

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

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Writing efficient code that handles large data and tight constraints

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Create new reusable skills from conversation context

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Systematic approach to diagnosing and fixing errors

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Thorough verification of completed work before declaring done

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Best practices for creating research diagrams with Excalidraw MCP tools

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Guidelines for writing well-structured, cited research reports

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Comprehensive data analysis skill for CSV files using Python and pandas

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