arcgispro-cli 0.1.3

CLI tool for inspecting ArcGIS Pro session exports

ArcGIS Pro CLI

Make ArcGIS Pro sessions observable for AI agents and automation tools.

Quick Start

pip install arcgispro-cli
arcgispro install

That's it! The install command launches the add-in installer. Click "Install Add-In" and restart ArcGIS Pro.

How It Works

1. Open a project in ArcGIS Pro

2. Click Snapshot in the ProExporter ribbon tab

3. A .arcgispro/ folder is created next to your .aprx file containing:

   • Project metadata (maps, layouts, geodatabases)
   • Layer details (fields, feature counts, visibility, symbology type)
   • Standalone tables and data connections
   • Map/layout images as PNG
   • Markdown summaries for AI consumption

4. Use the CLI to inspect exports:

   cd /path/to/your/project
   arcgispro inspect
   

CLI Commands

Command	Description
arcgispro install	Install the ProExporter add-in
arcgispro uninstall	Show uninstall instructions
arcgispro inspect	Print human-readable summary
arcgispro dump	Validate context JSON files
arcgispro images	Validate exported images
arcgispro snapshot	Assemble full snapshot
arcgispro clean	Remove generated files
arcgispro open	Select active project

Requirements

• Windows 10/11
• ArcGIS Pro 3.x
• Python 3.9+

Development

To build the add-in from source, you'll need:

• Visual Studio 2022 with ArcGIS Pro SDK extension
• .NET 8 SDK

# Clone and install CLI in dev mode
git clone https://github.com/danmaps/arcgispro_cli.git
cd arcgispro_cli/cli
pip install -e .

# Build add-in in Visual Studio
# Open ProExporter/ProExporter.sln
# Build → Build Solution (Release)

License

MIT

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Using with AI Agents

This tool is designed to make ArcGIS Pro sessions observable for AI coding assistants. Here's how to use it with popular CLI-based agents.

What Gets Exported

When you click Snapshot in ArcGIS Pro, the .arcgispro/ folder contains:

.arcgispro/
├── meta.json              # Export timestamp, tool version
├── context/
│   ├── project.json       # Project name, path, geodatabases
│   ├── maps.json          # Map names, spatial references, scales
│   ├── layers.json        # Full layer details with field schemas
│   ├── tables.json        # Standalone tables
│   ├── connections.json   # Database connections
│   └── layouts.json       # Print layouts
├── images/
│   ├── map_*.png          # Screenshots of each map view
│   └── layout_*.png       # Screenshots of each layout
└── snapshot/
    └── context.md         # Human-readable summary (best for AI)

Claude Code / Copilot CLI / Gemini CLI

These tools can read files from your working directory. Just navigate to your ArcGIS Pro project folder:

cd /path/to/your/project
arcgispro inspect   # Verify exports exist

# Then start your AI session
claude               # or: copilot, gemini

Example prompts:

Read .arcgispro/snapshot/context.md and summarize what layers are in this project.

Look at .arcgispro/context/layers.json and tell me which layers have 
more than 100,000 features.

Based on the field schemas in .arcgispro/context/layers.json, write a 
Python script using arcpy to calculate a new field.

Look at .arcgispro/images/map_Map.png and describe what you see.

Tips for Best Results

1. Run arcgispro snapshot before starting your AI session - ensures context is fresh

2. Point the agent to context.md first - it's a concise summary:

   Read .arcgispro/snapshot/context.md to understand my ArcGIS Pro project.
   

3. Use layers.json for detailed field info - includes field names, types, and aliases:

   What fields are available in the "parcels" layer? Check .arcgispro/context/layers.json
   

4. Share images for visual context - map screenshots help AI understand your data:

   Look at .arcgispro/images/map_Map.png - what type of data is being displayed?
   

Automated Workflows

You can script exports for CI/CD or batch processing:

# Export context from Pro (requires clicking Snapshot in Pro first)
# Then validate and use in automation:
arcgispro dump && arcgispro images && echo "Exports valid"

# Clean up after processing
arcgispro clean --all

Custom Agent Integration

The JSON files are designed for programmatic access:

import json
from pathlib import Path

context_dir = Path(".arcgispro/context")
layers = json.loads((context_dir / "layers.json").read_text(encoding="utf-8-sig"))

for layer in layers:
    print(f"{layer['name']}: {layer.get('featureCount', 'N/A')} features")
    for field in layer.get('fields', []):
        print(f"  - {field['name']} ({field['fieldType']})")