computer-science-algorithms Guide
Choosing or implementing an algorithm or data structure — asymptotic complexity, data-structure selection, sorting & searching, dynamic programming, graph algorithms, divide & conquer, greedy algorithms, string/sequence algorithms, and the at-scale toolbox (Bloom filters, HyperLogLog, Count-Min Sketch, reservoir sampling, consistent hashing, external merge sort, Aho-Corasick, MinHash/LSH). Trigger on tasks involving "what's the right algorithm for…", performance-critical code, code with nested loops over the same input, recursive solutions, shortest-path / scheduling / matching / DP problems, code review for accidental O(n²) blowup, and any "how do I do X at scale / on a stream / without enough RAM" question — even if the user doesn't explicitly mention "algorithm" or "complexity."
When to use computer-science-algorithms
Choosing or implementing an algorithm or data structure — asymptotic complexity, data-structure selection, sorting & searching, dynamic programming, graph algorithms, divide & conquer, greedy algorithms, string/sequence algorithms, and the at-scale toolbox (Bloom filters, HyperLogLog, Count-Min Sketch, reservoir sampling, consistent hashing, external merge sort, Aho-Corasick, MinHash/LSH). Trigger on tasks involving "what's the right algorithm for…", performance-critical code, code with nested loops over the same input, recursive solutions, shortest-path / scheduling / matching / DP problems, code review for accidental O(n²) blowup, and any "how do I do X at scale / on a stream / without enough RAM" question — even if the user doesn't explicitly mention "algorithm" or "complexity."
How to use computer-science-algorithms
computer-science-algorithms is a Claude skill in the SKILL.md format. Add it to your Claude environment from the source repository below, then it activates as a user-invocable skill when your task matches its description.