complexity-optimizer
Skill16 starsChanged 5 months agoMITView on GitHub
Analyze or improve codebase complexity and performance hotspots without broad rewrites. Use when reviewing nested loops, repeated scans, N+1 queries, rendering churn, excessive recomputation, slow tests, large-input paths, memory pressure, or requests to reduce complexity while preserving behavior and tests.
3 other projects use a version of this.
Adopted by
Most recently taken up by
- Kappaemme-git/codex-complexity-optimizertheir own version, first seen Oct 8, 2026
- themusecatcher/ai-coding-kittheir own version, first seen Sep 15, 2026
- langgenius/mosoo-skillstheir own version, first seen Jun 4, 2026
Other versions3 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 3
- Kappaemme-git/codex-complexity-optimizer★ 913same name
- langgenius/mosoo-skills★ 2same name
- themusecatcher/ai-coding-kit★ 2same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 33
Before editing, preserve behavior with existing tests, a focused regression test, a fixture, or a clear invariant.
- Distinctive: line 40
avoid caches without invalidation strategy.
- Distinctive: line 41
Run narrow checks first, then broader relevant checks.
- Distinctive: line 59
before/after complexity estimates.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Complexity Optimizer
Optimize only when behavior is understood and can be preserved. A small measured improvement beats a clever rewrite.
Modes
- Report mode: rank opportunities and do not edit.
- Implementation mode: change scoped code after identifying a repro, test, benchmark, or reviewable invariant.
- Audit mode: scan broad areas, then inspect only the highest-impact leads.
Workflow
- Establish scope: language, framework, hot paths, data sizes, tests, build command, and user-facing risk.
- Find leads: nested scans, repeated filtering, loops inside render paths, N+1 database/API calls, redundant serialization, unbounded recursion, cache misses, and avoidable work in hooks or lifecycle methods.
- Rank by likely impact and blast radius. Treat static findings as leads, not proof.
- For each serious finding, record:
- file and location;
- current pattern;
- estimated current complexity;
- proposed change;
- expected complexity after change;
- correctness risk;
- verification needed.
- Before editing, preserve behavior with existing tests, a focused regression test, a fixture, or a clear invariant.
- Optimize conservatively:
- replace repeated linear lookup with maps or sets when equality is stable;
- pre-index or group data before joins;
- batch database/API access while preserving tenant, permission, filtering, ordering, and pagination;
- memoize derived UI data only when inputs are stable;
- virtualize or paginate large rendered collections;
- avoid caches without invalidation strategy.
- Run narrow checks first, then broader relevant checks.
Safety Checklist
Before finalizing:
- output ordering is preserved or intentionally changed;
- duplicates and null/missing values are handled;
- mutation and object identity assumptions are not broken;
- authorization and tenant filters survive batching;
- cache invalidation is explicit;
- the original performance or failure signal was rerun.
Final Report
Include:
- top findings or changed files;
- before/after complexity estimates;
- verification commands and results;
- residual risks and missing measurement gaps.
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