arch-analysis

Bottleneck identification in LangGraph analyzes node-level metrics across latency, cost, and accuracy to pinpoint which components slow execution or increase expenses. The analysis measures your current graph structure and performance baselines, then surfaces specific issues like sequential processing or inefficient RAG patterns.

Yes. LangGraph architecture analysis generates 3-5 diverse, actionable improvement proposals tailored to your graph's specific bottlenecks. Each proposal targets different optimization angles—parallelization, efficiency gains, cost reduction—ready for parallel exploration and evaluation.

Performance analysis measures latency, cost, and accuracy across your LangGraph application's nodes and execution flow. It establishes baselines from your current graph, then evaluates how proposed architectural changes would impact each metric.

Architecture analysis produces an analysis report detailing bottlenecks and an improvement_proposals document describing 3-5 concrete changes with constraints and implementation details. Feed these proposals to implementation and evaluation tools to test and measure their actual impact.

No. Architecture analysis automates diagnosis by examining your live graph structure, performance baselines, and node metrics directly. It eliminates manual code sifting and log inspection, surfacing root causes and improvement strategies without requiring deep manual analysis.

Proposals address diverse optimization angles: sequential-to-parallel conversions, RAG efficiency improvements, cost reduction strategies, latency optimization, and accuracy enhancements. Each proposal is independently actionable and evaluated against your performance baselines.