Babysitter dp-optimizer

Apply advanced DP optimizations automatically

install

source · Clone the upstream repo

git clone https://github.com/a5c-ai/babysitter

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/algorithms-optimization/skills/dp-optimizer" ~/.claude/skills/a5c-ai-babysitter-dp-optimizer && rm -rf "$T"

manifest: library/specializations/algorithms-optimization/skills/dp-optimizer/SKILL.md

DP Optimizer Skill

Purpose

Apply advanced dynamic programming optimizations to improve time and space complexity of DP solutions.

Capabilities

Convex hull trick detection and application
Divide and conquer optimization
Knuth optimization
Monotonic queue/deque optimization
Alien's trick / WQS binary search
Rolling array optimization
Bitmask compression

Target Processes

dp-state-optimization
advanced-dp-techniques
complexity-optimization

Optimization Techniques

Time Optimizations

Convex Hull Trick: O(n^2) -> O(n log n) for certain recurrences
Divide & Conquer: O(n^2 k) -> O(n k log n) when optimal j is monotonic
Knuth Optimization: O(n^3) -> O(n^2) for certain interval DP
Monotonic Queue: O(n*k) -> O(n) for sliding window DP

Space Optimizations

Rolling Array: O(n*m) -> O(m) when only previous row needed
Bitmask Compression: Reduce state space with bit manipulation

Input Schema

{
  "type": "object",
  "properties": {
    "dpCode": { "type": "string" },
    "stateDefinition": { "type": "string" },
    "transitions": { "type": "string" },
    "currentComplexity": { "type": "string" },
    "targetComplexity": { "type": "string" },
    "optimizationType": {
      "type": "string",
      "enum": ["auto", "convexHull", "divideConquer", "knuth", "monotonic", "space"]
    }
  },
  "required": ["dpCode", "optimizationType"]
}

Output Schema

{
  "type": "object",
  "properties": {
    "success": { "type": "boolean" },
    "optimizedCode": { "type": "string" },
    "optimizationApplied": { "type": "string" },
    "newComplexity": { "type": "string" },
    "explanation": { "type": "string" }
  },
  "required": ["success"]
}