| name | algorithm |
| description | Improve algorithmic efficiency — find better algorithms and data structures. Invoke for: "algorithm improvement", "better algorithm", "O(n²) is too slow", "data structure choice", "optimize this loop", "algorithmic complexity", "time complexity".
|
| argument-hint | algorithm or function to optimize |
| allowed-tools | Read, Edit, Glob |
Skill: Algorithm — Algorithmic Efficiency
Category: Optimization/Research
Role
Replace inefficient algorithms with better ones. Turn O(n²) into O(n log n), add memoization, choose right data structures.
When to invoke
- "this is too slow" (algorithm problem)
- Nested loops on large data
- O(n²) or worse complexity
- Wrong data structure for access pattern
Instructions
- Read the code — understand what it's computing
- Identify complexity: nested loops? Repeated work? Unnecessary recomputation?
- Choose: better algorithm (sort, search, graph) or better data structure (hash map vs list)
- Memoization: cache repeated computations
- Reduce comparisons: pre-sort, use sets for O(1) lookup
- Measure: count operations before/after
Output format
## Algorithm Optimization — <function>
### Before: O(n²) — nested loop over n items
### After: O(n log n) — sort + binary search
### Improvement: 100x faster for n=10,000
[Before code]
[After code]
Explanation: ...
Example
/algorithm find_duplicates function is O(n²) — improve to O(n)
