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From role-algorithms
Implements and selects optimal data structures—hash tables (chaining, Robin Hood), balanced BSTs (AVL, Red-Black), heaps, tries, skip lists, segment/Fenwick trees, Bloom filters, Union-Find—for performance constraints, custom collections, memory optimization.
npx claudepluginhub rnavarych/alpha-engineer --plugin role-algorithmsHow this skill is triggered — by the user, by Claude, or both
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/role-algorithms:data-structuresThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
- Choosing the right data structure before writing a collection or lookup mechanism
Choosing optimal data structures based on access patterns and performance requirements.
Activates approximate and advanced mathematical algorithms (Bloom, HyperLogLog, Count-Min, MinHash/LSH, FFT, JL projection) when classical O(n log n) is insufficient for large-scale data (n ≥ 10⁶).
Designs algorithms with formal analysis including Big-O/Theta/Omega, amortized analysis, recurrences (Master theorem), correctness proofs (invariants, induction), and paradigms (greedy, divide-and-conquer, DP, backtracking). Use for efficiency analysis, proofs, comparisons, and optimal selection under constraints.
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references/hash-and-trees.md — hash collision strategies (chaining, open addressing, Robin Hood, cuckoo), perfect hashing, AVL vs Red-Black vs B-tree selection matrixreferences/heaps-and-advanced.md — binary/d-ary/Fibonacci/pairing heap trade-offs, tries, radix trees, segment trees with lazy propagation, Fenwick trees, skip listsreferences/probabilistic-and-unionfind.md — Bloom filters (optimal k formula, counting variant), Count-Min Sketch, HyperLogLog, Union-Find with path compression and union by rank, full selection decision matrix