performance-analysis
Systematic performance engineering: baseline measurement, profiling, bottleneck diagnosis, and evidence-based optimization guidance for high-performance applications.
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162 skills found
Systematic performance engineering: baseline measurement, profiling, bottleneck diagnosis, and evidence-based optimization guidance for high-performance applications.
CMMI-based SDLC router providing process guidance, requirements management, architectural decision support, quality assurance, and governance for GitHub and Azure DevOps workflows.
Deep document structure analysis and intelligent content extraction for knowledge bases.
Systematically extract insights, decisions, and constraints from research documents, technical papers, and architectural design files.
Automates the creation and maintenance of CLAUDE.md files. It monitors codebase evolution and keeps project memory in sync with file changes, structure, and build commands.
Compiler-accurate semantic code analysis via LSP. Navigate definitions, references, and implementations, perform workspace-wide renames, and get file outlines for Python, Rust, Go, TypeScript/JS, and Java.
Analyze GA4 and GSC performance data with automated benchmarks, status indicators, and actionable content optimization insights.
Analyze GitHub repository structure, documentation, dependencies, and contributor patterns for codebase health and development insights.
Monitor project progress, analyze active tracks, and identify blockers within your development workspace.
Process massive files and large codebases (10M+ tokens) by recursively chunking, sub-querying, and aggregating results to overcome LLM context limits.
Reverse-engineering specialist for codebase analysis, dependency mapping, and specification extraction from legacy or undocumented systems.
Decompose financial variances into drivers with narrative explanations and waterfall analysis. Optimize budget vs. actual reporting, P&L commentary, and forecast reconciliation.