Babysitter advanced-ds-library
Provide implementations of advanced data structures
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 "$T/library/specializations/algorithms-optimization/skills/advanced-ds-library" ~/.claude/skills/a5c-ai-babysitter-advanced-ds-library && rm -rf "$T"
manifest:
library/specializations/algorithms-optimization/skills/advanced-ds-library/SKILL.mdsource content
Advanced Data Structures Library Skill
Purpose
Provide implementations and guidance for advanced data structures commonly needed in competitive programming and complex algorithmic problems.
Capabilities
- Treaps, Splay trees, Link-cut trees
- Persistent data structures
- Wavelet trees
- Heavy-light decomposition
- Centroid decomposition
- Rope data structure
- Order statistics tree
Target Processes
- data-structure-implementation
- advanced-graph-algorithms
- cp-library-creation
Data Structure Catalog
Balanced BSTs
- Treap (randomized BST)
- Splay Tree (self-adjusting)
- AVL Tree
- Red-Black Tree
Tree Decomposition
- Heavy-Light Decomposition
- Centroid Decomposition
- Euler Tour Technique
Advanced Structures
- Link-Cut Trees (dynamic trees)
- Wavelet Tree (range queries)
- Persistent Segment Tree
- Rope (string with fast operations)
Input Schema
{ "type": "object", "properties": { "dataStructure": { "type": "string" }, "operations": { "type": "array" }, "language": { "type": "string", "enum": ["cpp", "python", "java"] }, "includeTests": { "type": "boolean", "default": false } }, "required": ["dataStructure"] }
Output Schema
{ "type": "object", "properties": { "success": { "type": "boolean" }, "code": { "type": "string" }, "complexity": { "type": "object" }, "usage": { "type": "string" }, "applications": { "type": "array" } }, "required": ["success"] }