Free SKILL.md scraped from GitHub. Clone the repo or copy the file directly into your Claude Code skills directory.
npx versuz@latest install a5c-ai-babysitter-library-specializations-algorithms-optimization-skills-dp-optimigit clone https://github.com/a5c-ai/babysitter.gitcp babysitter/SKILL.MD ~/.claude/skills/a5c-ai-babysitter-library-specializations-algorithms-optimization-skills-dp-optimi/SKILL.md---
name: dp-optimizer
description: Apply advanced DP optimizations automatically
allowed-tools:
- Read
- Write
- Grep
- Glob
- Edit
---
# 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
1. **Convex Hull Trick**: O(n^2) -> O(n log n) for certain recurrences
2. **Divide & Conquer**: O(n^2 k) -> O(n k log n) when optimal j is monotonic
3. **Knuth Optimization**: O(n^3) -> O(n^2) for certain interval DP
4. **Monotonic Queue**: O(n*k) -> O(n) for sliding window DP
### Space Optimizations
1. **Rolling Array**: O(n*m) -> O(m) when only previous row needed
2. **Bitmask Compression**: Reduce state space with bit manipulation
## Input Schema
```json
{
"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
```json
{
"type": "object",
"properties": {
"success": { "type": "boolean" },
"optimizedCode": { "type": "string" },
"optimizationApplied": { "type": "string" },
"newComplexity": { "type": "string" },
"explanation": { "type": "string" }
},
"required": ["success"]
}
```