DP State Designer Skill

Purpose

Assist in designing optimal dynamic programming states, transitions, and optimizations for complex DP problems.

Capabilities

• •Identify subproblem structure from problem description
• •Suggest state representations (dimensions, parameters)
• •Derive transition formulas
• •Identify optimization opportunities (rolling array, bitmask compression)
• •Generate state space complexity estimates
• •Detect overlapping subproblems

Target Processes

• •dp-pattern-matching
• •dp-state-optimization
• •dp-transition-derivation
• •advanced-dp-techniques

DP Design Framework

1. •Subproblem Identification: What smaller problems compose the solution?
2. •State Definition: What parameters uniquely identify a subproblem?
3. •Transition Formula: How do we combine subproblem solutions?
4. •Base Cases: What are the trivial subproblems?
5. •Computation Order: In what order should we solve subproblems?
6. •Space Optimization: Can we reduce memory usage?

Input Schema

{
  "type": "object",
  "properties": {
    "problemDescription": { "type": "string" },
    "constraints": { "type": "object" },
    "examples": { "type": "array" },
    "requestType": {
      "type": "string",
      "enum": ["fullDesign", "stateOnly", "transitions", "optimize"]
    }
  },
  "required": ["problemDescription", "requestType"]
}

Output Schema

{
  "type": "object",
  "properties": {
    "success": { "type": "boolean" },
    "state": {
      "type": "object",
      "properties": {
        "definition": { "type": "string" },
        "parameters": { "type": "array" },
        "complexity": { "type": "string" }
      }
    },
    "transitions": { "type": "array" },
    "baseCases": { "type": "array" },
    "optimizations": { "type": "array" }
  },
  "required": ["success"]
}