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genpark-evol-instruct-prompt-complexity-enhancer-skill

mcp
Guvenlik Denetimi
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SUMMARY

Evolutionary prompt mutation algorithm adding constraints, deepening reasoning, and increasing problem complexity

README.md

genpark-evol-instruct-prompt-complexity-enhancer-skill

An algorithmic prompt mutation engine implementing the WizardLM Evol-Instruct paradigm. Synthesizes high-complexity training data from simple seed instructions through structured mutation templates.

Architecture

flowchart TD
    Seed[Seed Instruction] --> Mutator[EvolInstructMutator]
    Mutator --> T1[Deepen Reasoning]
    Mutator --> T2[Add Constraints]
    Mutator --> T3[Concretize]
    Mutator --> T4[Increase Reasoning Steps]
    Mutator --> T5[In-Breadth Evolution]
    T2 --> Evaluator[Complexity Scoring Engine]
    Evaluator --> Mutated[High-Complexity Benchmark Dataset]

Features

  • Deterministic Complexity Scoring: Quantifies lexical length, logical connectives, and constraints.
  • 5 Mutation Vectors: Deepens reasoning, adds technical constraints, concretizes abstract ideas, expands step count, and expands cross-domain analogies.
  • 100% Python Standard Library: Zero pip dependencies.
  • Model Context Protocol (MCP): Native stdio server support.

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