cursor-performance-tuning
Optimize Cursor IDE performance: reduce memory usage, speed up indexing, tune AI features, and manage extensions for large codebases. Triggers on "cursor performance", "cursor slow", "cursor optimization", "cursor memory", "speed up cursor", "cursor lag".
Best use case
cursor-performance-tuning is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Optimize Cursor IDE performance: reduce memory usage, speed up indexing, tune AI features, and manage extensions for large codebases. Triggers on "cursor performance", "cursor slow", "cursor optimization", "cursor memory", "speed up cursor", "cursor lag".
Teams using cursor-performance-tuning should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/cursor-performance-tuning/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How cursor-performance-tuning Compares
| Feature / Agent | cursor-performance-tuning | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Optimize Cursor IDE performance: reduce memory usage, speed up indexing, tune AI features, and manage extensions for large codebases. Triggers on "cursor performance", "cursor slow", "cursor optimization", "cursor memory", "speed up cursor", "cursor lag".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Cursor Performance Tuning
Diagnose and fix Cursor IDE performance issues. Covers editor optimization, indexing tuning, extension auditing, AI feature configuration, and strategies for large codebases.
## Performance Diagnostic Workflow
```
Step 1: Identify bottleneck
├── Editor lag? → Step 2 (Editor settings)
├── High CPU? → Step 3 (Extension audit)
├── Slow AI? → Step 4 (AI tuning)
└── Memory? → Step 5 (Memory management)
Step 2: Editor settings
├── Disable minimap, breadcrumbs
├── Reduce file watcher scope
└── Increase memory limits
Step 3: Extension audit
├── Profile running extensions
├── Disable heavy extensions
└── Use workspace-scoped disabling
Step 4: AI feature tuning
├── Optimize .cursorignore
├── Use faster models
└── Manage chat history
Step 5: Memory management
├── Close unused workspace folders
├── Limit open editor tabs
└── Clear caches
```
## Editor Optimization
### settings.json Performance Settings
```json
{
// Disable visual features for speed
"editor.minimap.enabled": false,
"editor.renderWhitespace": "none",
"editor.guides.bracketPairs": false,
"breadcrumbs.enabled": false,
"editor.occurrencesHighlight": "off",
"editor.matchBrackets": "never",
"editor.folding": false,
"editor.glyphMargin": false,
// Reduce file watching scope
"files.watcherExclude": {
"**/node_modules/**": true,
"**/.git/objects/**": true,
"**/.git/subtree-cache/**": true,
"**/dist/**": true,
"**/build/**": true,
"**/coverage/**": true,
"**/.next/**": true,
"**/target/**": true
},
// Exclude from search and explorer
"files.exclude": {
"**/node_modules": true,
"**/.git": true,
"**/dist": true,
"**/build": true
},
// Memory limits
"files.maxMemoryForLargeFilesMB": 4096,
// Reduce auto-save overhead
"files.autoSave": "onFocusChange",
// Limit search results
"search.maxResults": 5000
}
```
### Disable Animations
```json
{
"workbench.list.smoothScrolling": false,
"editor.smoothScrolling": false,
"editor.cursorSmoothCaretAnimation": "off",
"terminal.integrated.smoothScrolling": false
}
```
## Extension Audit
### Profile Running Extensions
`Cmd+Shift+P` > `Developer: Show Running Extensions`
This shows:
- Extension name
- Activation time (ms)
- Profile CPU time
Sort by activation time. Extensions taking > 500ms are worth investigating.
### Process Explorer
`Cmd+Shift+P` > `Developer: Open Process Explorer`
Shows per-process CPU and memory usage:
- Main window
- Extension host (all extensions combined)
- Individual extension processes
- Terminal processes
### Common High-Impact Extensions
| Extension | Impact | Mitigation |
|-----------|--------|------------|
| **GitLens** | CPU: high on large repos | Disable for repos > 50K commits or use lightweight mode |
| **Prettier** | CPU: triggers on every save | Set `"editor.formatOnSave": false`, format manually |
| **TypeScript** | Memory: large projects | Increase `"typescript.tsserver.maxTsServerMemory": 4096` |
| **ESLint** | CPU: validates on type | Set `"eslint.run": "onSave"` instead of "onType" |
| **Spell Checker** | CPU: large files | Add exclusion patterns for generated files |
| **Import Cost** | CPU: recalculates on change | Disable for projects with many imports |
### Disable Per Workspace
Right-click extension > `Disable (Workspace)`. This keeps the extension available for other projects while removing it from the current slow one.
## AI Feature Tuning
### Indexing Optimization
The biggest performance lever for AI features:
```gitignore
# .cursorignore -- aggressive exclusion for large projects
node_modules/
dist/
build/
.next/
out/
target/
coverage/
.turbo/
.cache/
__pycache__/
*.pyc
venv/
.venv/
# Generated code
*.min.js
*.min.css
*.bundle.js
*.d.ts.map
*.tsbuildinfo
# Data files
*.csv
*.json.gz
*.parquet
*.sqlite
*.sql
# Lock files
package-lock.json
yarn.lock
pnpm-lock.yaml
Cargo.lock
# Media
*.png
*.jpg
*.gif
*.svg
*.mp4
*.woff2
# Documentation build output
docs/dist/
docs/.vitepress/dist/
```
### Tab Completion Speed
Tab completion is fast by design (~100ms), but can feel slow if:
- The file is very large (> 10K lines): split the file
- Many extensions are running: audit extensions
- Network is slow: Tab requires network for model inference
### Chat/Composer Response Time
| Factor | Impact | Fix |
|--------|--------|-----|
| Model choice | Opus/o1 are slower than Sonnet/GPT-4o | Use faster models for simple tasks |
| Context size | More @-mentions = slower | Use @Files not @Codebase when possible |
| Conversation length | Long chats slow down | Start new chat frequently |
| Server load | Peak hours are slower | Use off-peak or BYOK |
### Managing Chat History
Long chat sessions consume memory and slow down responses:
```
Signs of chat-related slowdown:
- Typing lag in the chat input
- Editor becomes sluggish after extended chat session
- AI responses take progressively longer
Fix:
1. Start a new chat (Cmd+N in chat panel)
2. Close old chat tabs
3. One topic per chat session
```
## Large Codebase Strategies
### For Projects > 50K Files
```
1. Open specific packages, not the whole monorepo
cursor packages/api/ # Not: cursor .
2. Aggressive .cursorignore (see above)
3. Multi-root workspace with only active packages
File > Add Folder to Workspace (selectively)
4. Disable codebase indexing if not needed
Cursor Settings > Features > Codebase Indexing > off
(You lose @Codebase but gain performance)
5. Increase system resources
Close other Electron apps (Slack, Teams, Discord)
Increase swap space on Linux
```
### Linux File Watcher Limits
```bash
# Check current limit
cat /proc/sys/fs/inotify/max_user_watches
# Increase (required for large projects)
echo "fs.inotify.max_user_watches=524288" | sudo tee -a /etc/sysctl.conf
sudo sysctl -p
```
### Memory Monitoring
```bash
# macOS: Monitor Cursor memory usage
top -pid $(pgrep -f "Cursor")
# Linux: Monitor Cursor processes
ps aux | grep -i cursor | sort -rn -k4
# If memory exceeds 4GB consistently:
# 1. Close unused workspace folders
# 2. Limit open editor tabs to ~20
# 3. Restart Cursor daily during heavy use
```
## Cache Management
### Clear Caches
```bash
# macOS
rm -rf ~/Library/Application\ Support/Cursor/Cache/
rm -rf ~/Library/Application\ Support/Cursor/CachedData/
rm -rf ~/Library/Application\ Support/Cursor/Code\ Cache/
# Linux
rm -rf ~/.config/Cursor/Cache/
rm -rf ~/.config/Cursor/CachedData/
rm -rf ~/.config/Cursor/Code\ Cache/
```
Restart Cursor after clearing. Caches rebuild automatically.
### Database Maintenance
Cursor stores extension data in SQLite databases. If the storage directory grows large:
```bash
# Check size (macOS)
du -sh ~/Library/Application\ Support/Cursor/
# If > 2GB, clearing Cache/ and CachedData/ usually reclaims most space
```
## Enterprise Considerations
- **Baseline performance**: Establish performance baselines for standard project sizes on team hardware
- **Hardware recommendations**: 16GB RAM minimum for large projects, 32GB for monorepos
- **Network performance**: AI features require low-latency internet. VPN routing can add 200-500ms per request
- **Standardized settings**: Distribute performance-optimized `settings.json` to all team members
## Resources
- [VS Code Performance Tips](https://code.visualstudio.com/docs/editor/editingevolved#_performance)
- [Cursor Forum - Performance](https://forum.cursor.com/c/help)
- [Codebase Indexing](https://docs.cursor.com/context/codebase-indexing)Related Skills
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