Agent skill · software engineering · microsoft
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
Why this skill is useful
Adds executable scripts for performance optimization and memory investigation in VS Code that are not available in public documentation.
What it needs
Requires @playwright/cli, bash, npx installed locally. About 11k tokens when loaded. Last updated 2026-08-07. 188,455 stars on the source repository.
What this skill does
VS Code Performance Workflow Drive a repeatable VS Code scenario, collect memory/performance artifacts, verify that the scenario actually happened, then hand the resulting heap snapshots to the generic heap-snapshot-analysis skill when object-level investigation is needed. When to Use User describes a VS Code workflow and asks whether it leaks or grows memory User asks the agent to launch VS Code, drive a scenario, and capture heap snapshots User asks to run the Chat memory smoke runner bundled with this skill User wants screenshots, summary.json, renderer heap samples, and targeted .heapsnapshot files for one scenario User wants a new automation runner for a non-Chat VS Code scenario Do not use this skill when snapshots already exist and the user only wants heap object/retainer analysis. Use heap-snapshot-analysis directly. The Story 1. Define the scenario. Write down one warmup action, one repeatable iteration, and one quiescent point where it is fair to force GC and sample memory. 2. Develop the automation. Start with a tiny no-snapshot run. If it fails or the UI state is uncertain, keep the Code window open, connect @playwright/cli to the same CDP port, take workspace-local screenshots, inspect snapshots, and update the runner's selectors/waits. 3. Run a fast smoke. Disable heap snapshots first. Prove the scenario completes and the artifact summary says what you think it says. 4. Capture targeted snapshots. Snapshot a warmed-up baseline and a later iteration. Do not snapshot every sample unless necessary; snapshots are huge and slow. 5. Verify the run. Inspect summary.json and screenshots. Do not analyze a failed login, trust prompt, stuck progress row, or wrong UI state. 6. Analyze snapshots. Switch to heap-snapshot-analysis for compare scripts, object grouping, and retainer paths. 7. Fix and verify. After identifying leaks, make product-code fixes. Then rerun the same scenario with the same snapshot labels and compare like-for-like. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills microsoft/auto-perf-optimize