Individual skill
complexity-optimizer
Analyze a software codebase for algorithmic complexity and performance hotspots, then propose or implement safe optimizations without breaking behavior. Use when the user asks to scan many files, find inefficient loops, nested iteration, repeated scans, costly rendering/recomputation, N+1 queries, avoidable O(n^2) or O(n) operations, or reduce complexity such as O(n^2) to O(n log n) / O(n), while preserving tests, APIs, outputs, and maintainability.
skills/.experimental/complexity-optimizer/SKILL.md
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- Last checked
- Nov 5, 2026
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- Repository stars (not skill ratings)
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- Repository last updated
- Aug 15, 2026
- License
- MIT
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- engineering Derived category
- operations Derived category
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SKILL.mdcore · 8,966 bytesSKILL.mdcore · 8,966 bytesSKILL.mdcore · 8,966 byteshooks.jsonasset · 411 bytesmetadata.jsonasset · 904 bytesreferences/false-positives.mddoc · 5,092 bytesreferences/optimization-playbook.mddoc · 2,996 bytesreferences/report-template.mddoc · 797 bytesscripts/_sections.mddoc · 3,032 bytesscripts/analyze_complexity.pyruns · 16,444 bytesscripts/test_analyze_complexity.pyruns · 10,592 bytes
Read excerpt
# Complexity Optimizer
Find algorithmic complexity hotspots in a codebase and produce a structured report. Optionally implement low-risk optimizations after explicit consent.
## When to Apply
Use this skill when the user asks to:
- Analyze, audit, scan, or review a codebase for performance hotspots or algorithmic complexity
- Find inefficient loops, nested iteration, N+1 queries, sort-in-loop, render-path recomputation
- Reduce complexity (e.g. O(n^2) → O(n log n) or O(n))
- "Give me a report" on a codebase's complexity profile
Do not use this skill for:
- Micro-optimizations on cold code paths