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role-algorithms
Design provably correct, asymptotically optimal algorithms and data structures; analyze computational complexity with Big-O proofs; implement dynamic programming, graph algorithms, sorting/searching, numerical methods, and optimization solvers; optimize performance-critical code across paradigms like greedy, divide-and-conquer, and backtracking.
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npx claudepluginhub rnavarych/alpha-engineer --plugin role-algorithmsPopularity
Stars
Med: 0·Avg: 278
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Med: 0·Avg: 1
What's Inside
Skills8
role-algorithms:algorithm-design
/algorithm-design
Designs algorithms with formal analysis — Big-O/Theta/Omega, amortized analysis, recurrence relations (Master theorem), correctness proofs (loop invariants, induction, reduction), and paradigm selection (greedy, divide-and-conquer, dynamic programming, backtracking). Use when analyzing efficiency, proving correctness, comparing approaches, or selecting optimal algorithms for given constraints.
role-algorithms:computational-complexity
/computational-complexity
Analyzes computational complexity — P vs NP classification, NP-completeness proofs and reductions, approximation algorithms (PTAS, FPTAS) with provable guarantees, parameterized complexity (FPT, kernelization), randomized algorithms (Las Vegas, Monte Carlo), and practical heuristics for intractable problems. Use when classifying hardness, proving reductions, or selecting between exact and heuristic approaches.
role-algorithms:data-structures
/data-structures
Implements and selects optimal data structures — hash tables (chaining, open addressing, Robin Hood, cuckoo), balanced BSTs (AVL, Red-Black, B-trees), heaps (binary, Fibonacci, pairing), tries, skip lists, segment trees, Fenwick trees, Bloom filters, Count-Min Sketch, HyperLogLog, and Union-Find. Use when choosing structures for performance constraints, implementing custom collections, or optimizing memory access patterns.
role-algorithms:dynamic-programming
/dynamic-programming
Solves optimization problems using dynamic programming — top-down memoization, bottom-up tabulation, state space design, dimension reduction, bitmask DP, interval DP, tree DP (with rerooting), DP on DAGs, and convex hull trick / divide-and-conquer optimizations. Use when solving optimization problems with overlapping subproblems, implementing memoized solutions, or converting recursive solutions to iterative DP.
role-algorithms:graph-algorithms
/graph-algorithms
Implements graph algorithms — BFS/DFS traversal, shortest paths (Dijkstra, Bellman-Ford, Floyd-Warshall, A*, Johnson's), minimum spanning trees (Kruskal, Prim), topological sort, strongly connected components (Tarjan, Kosaraju), maximum flow (Ford-Fulkerson, Dinic), and bipartite matching (Hopcroft-Karp, Hungarian). Use when solving traversal, shortest path, network flow, connectivity, or scheduling problems.
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Version1.0.0
Released
LanguageShell
Stars13
Forks1
MaintenanceGood
LicenseMIT
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