Analyze codebases to detect performance bottlenecks and optimization opportunities.
npx skills add https://github.com/Sheldon-92/TAD --skill performance-sheldon-92
Please help me install this Agent Skill. Skill: Performance Source: https://github.com/Sheldon-92/TAD/tree/main/.tad/skills/performance Command: npx skills add https://github.com/Sheldon-92/TAD --skill performance-sheldon-92
Performance issues in codebases can cause latency, poor user experience, and wasted compute resources. This skill identifies bottlenecks in algorithms, memory usage, and database access patterns, and provides concrete optimization guidance.
Provide the target codebase path or files to analyze, and I will produce a performance review with concrete optimization recommendations.
High-intent search queries and answers about installing and using this skill.
Performance analysis detects inefficient algorithms and memory leaks by evaluating codebase hot paths. It targets loops and database operations to pinpoint O(n^2) hotspots, memory leaks, and unbounded growth using evidence-backed detection patterns.
Finding O(n^2) algorithms and memory leaks during code review requires profiling-oriented evaluation of data-heavy paths. The analysis enforces performance criteria to detect unbounded growth and database access bottlenecks with actionable remediation notes.
Yes, automated code analysis evaluates database operations and loops to find optimization opportunities. It enforces detection patterns across common hot paths and data-heavy modules to provide concrete guidance for performance improvements.
The best way to optimize code performance hotspots is applying evidence-backed recommendations from a full codebase analysis. This identifies bottlenecks across modules and services, justifying optimizations with benchmarks in deployment gates.
Performance profiling works effectively for batch operations and data-heavy paths by enforcing detection patterns. The analysis targets these common hot paths to identify unbounded growth and memory leaks with actionable remediation notes.
You should not use automated performance analysis when lacking a concrete codebase path for evaluation. The process requires target files to analyze modules and services, as it relies on evidence-backed detection patterns rather than theoretical design reviews.
foutoucourAudit code for performance bottlenecks across files and directories.
mouayadakelAnalyze code and database queries for performance regressions and anti-patterns.
PrepLabsAIGuide heap analysis and retention-path tracing for Java and Python memory leaks.
kunallimayeProfile software performance with perf, valgrind, strace, and hyperfine.
