Arcgis Performance
Analyzes ArcGIS Online/Enterprise performance metrics to identify bottlenecks and optimize map/application speed.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add arcgis-performance npx -- -y @trustedskills/arcgis-performance
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"arcgis-performance": {
"command": "npx",
"args": [
"-y",
"@trustedskills/arcgis-performance"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill optimizes ArcGIS map performance within AI agent workflows. It allows for efficient handling of large datasets, reduces rendering times, and improves the overall responsiveness of map interactions. The skill focuses on streamlining data loading and display to ensure a smooth user experience when working with complex geospatial information.
When to use it
- Analyzing large raster datasets: When processing satellite imagery or aerial photography that would otherwise cause slow load times.
- Creating interactive web mapping applications: To improve the responsiveness of map panning, zooming, and feature querying within an AI-powered application.
- Developing data visualization dashboards: For presenting complex geospatial data in a clear and performant manner to users interacting with an agent.
- Automating geoprocessing tasks: To accelerate workflows involving spatial analysis and data manipulation within ArcGIS.
Key capabilities
- Data streaming optimization
- Rendering performance enhancements
- Efficient feature querying
- Large dataset handling
Example prompts
- "Optimize the rendering of this 10,000-layer map."
- "Reduce the load time for this raster dataset by half."
- "Improve the responsiveness of feature queries on this map."
Tips & gotchas
This skill requires familiarity with ArcGIS and its mapping SDK. Ensure that your AI agent has access to a valid ArcGIS environment and appropriate data connections before attempting performance optimization.
Tags
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