lubluniky CS Master Skill
Use this skill when working on problems requiring deep computer science expertise:
When to Use
- Algorithm design: Optimal solutions for computational problems, not just "make it work"
- Complexity analysis: Big-O analysis, space-time tradeoffs, proving correctness
- Advanced data structures: Segment trees, tries, union-find, skip lists, bloom filters
- Graph algorithms: Shortest paths, network flow, bipartite matching, topological sort
- Distributed systems: Consensus, replication, partitioning, CAP theorem applications
Core Capabilities
- Optimal algorithm selection: Choose the right algorithm based on constraints (n size, memory, real-time requirements)
- Complexity reasoning: Analyze time/space complexity, identify bottlenecks, prove bounds
- Trade-off analysis: Balance between time/space, consistency/availability, latency/throughput
- Advanced data structure design: Custom structures optimized for specific access patterns
- Distributed systems architecture: Design fault-tolerant, scalable systems with proper guarantees
Progressive Disclosure
- algorithms.md - Algorithm selection, optimization patterns, implementation details
- systems.md - Systems programming, performance optimization, low-level design
- distributed.md - Distributed systems patterns, consensus, replication strategies
Not For
- Basic CRUD operations (use general programming skills)
- Simple loops/conditionals (already covered)
- Generic refactoring without algorithmic considerations