What problem does it solve? Node.js applications suffering from memory leaks, heap growth, high RSS, or out-of-memory crashes are hard to root-cause without structured heap evidence. This Skill guides the AI through a disciplined triage workflow that reuses existing heap assets, captures new heap sampling or snapshot data only when needed, and pinpoints the constructors or functions allocating the most memory. ## Core Features & Use Cases - Evidence-First Triage: Parses supplied asset IDs, local .heapprofile/.heapsnapshot paths, and heap summaries before triggering any new capture, avoiding redundant production overhead. - Controlled Heap Capture: Prefers low-overhead heap sampling over full heap snapshots, enforces exact blocking wait times via a bundled script, and monitors asynchronous asset summarization until ready. - Root-Cause Reporting: Identifies top allocators and retaining paths from asset summaries, downloads the full asset to .nsolid/assets/, and writes a structured markdown report on request. - Use Case: An on-call engineer receives an alert that a production Node.js service shows steadily growing RSS. The Skill locates the offending agent, captures a 30-second heap sample, summarizes it, names the leaking constructor, and saves the full heap profile for deeper inspection. ## Quick Start Ask the AI to diagnose why your Node.js app's memory keeps growing using N|Solid, providing the app name or an existing heap asset ID.
