How to Share the Egonex-AI Knowledge Graph with Your Team: 5 Proven Methods

Teams can share the Egonex-AI knowledge graph by distributing the generated .understand-anything/knowledge-graph.json file through version control, static hosting, direct file transfer, dashboard bundles, or CI/CD artifacts.

The Understand Anything plugin constructs a comprehensive knowledge graph for your codebase and persists it as a standard JSON file. When you need to share the Egonex-AI knowledge graph with a team, you are essentially distributing a plain text artifact produced by the analyzer pipeline in packages/core/src/analyzer/graph-builder.ts.

Where the Knowledge Graph Is Stored

After the analysis completes, the system writes the graph structure to two key locations:

• .understand-anything/knowledge-graph.json — the primary output in your project root
• packages/dashboard/public/knowledge-graph.json — a UI-ready copy bundled with the dashboard

Because the format is plain JSON, you can share it using any standard file-sharing workflow that handles text files.

Five Methods to Share the Egonex-AI Knowledge Graph with Your Team

Commit the JSON to Your Repository

Add the generated knowledge-graph.json to version control. This approach keeps the graph synchronized with your source code, enables diff-based reviews, and ensures every teammate receives the latest analysis when they pull the repo. This method works best for small-to-medium teams that already version-control generated artifacts.

Serve via a Static HTTP Endpoint

Host the knowledge-graph.json on any static file server such as GitHub Pages, an internal CDN, or a lightweight Express/Nginx endpoint. This creates a single source of truth accessible via URL without requiring every collaborator to pull the repository. This is ideal when you want to embed the graph in separate web applications or provide access to non-developers.

Export and Share the File Directly

After running the analyzer, copy the JSON file and distribute it through existing collaboration tools like Slack, Teams, email, or shared drives. This works best for quick ad-hoc sharing or when the graph is too large to push to the main repository.

Distribute the Dashboard Bundle

The dashboard UI consumes the graph from packages/dashboard/public/knowledge-graph.json. Zip the entire packages/dashboard/public directory to ship a self-contained, ready-to-run UI snapshot to non-technical stakeholders. This bundle includes the JSON and all static assets required for visualization.

Reference as CI/CD Pipeline Artifacts

Configure your pipeline to upload the JSON as an artifact after each analysis run. Downstream jobs can download and process the graph for documentation generation, testing, or analytics. This method suits automated workflows where subsequent jobs depend on the graph data.

Code Examples for Sharing Workflows

Commit and Push the Graph

# Run the full analysis (generates .understand-anything/knowledge-graph.json)

understand --full

# Add the generated graph to Git

git add .understand-anything/knowledge-graph.json
git commit -m "Add latest knowledge graph"
git push origin main

Serve with Minimal Node.js Server

// server.mjs
import { createServer } from 'node:http';
import { readFile } from 'node:fs/promises';
import { fileURLToPath } from 'node:url';

const __dirname = new URL('.', import.meta.url).pathname;

createServer(async (req, res) => {
  if (req.url === '/knowledge-graph.json') {
    const data = await readFile(`${__dirname}/.understand-anything/knowledge-graph.json`);
    res.writeHead(200, { 'Content-Type': 'application/json' });
    res.end(data);
  } else {
    res.writeHead(404);
    res.end('Not found');
  }
}).listen(3000);

Upload as GitHub Action Artifact

# .github/workflows/graph.yml

name: Build Knowledge Graph
on: [push]

jobs:
  build-graph:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - run: pnpm install && pnpm run understand --full
      - uses: actions/upload-artifact@v3
        with:
          name: knowledge-graph
          path: .understand-anything/knowledge-graph.json

Best Practices for Team Sharing

Keep JSON Output Deterministic

Run the analysis with consistent options and commit the resulting file to avoid noisy diffs in version control. The graph structure produced by packages/core/src/analyzer/graph-builder.ts should remain stable across runs when source code hasn't changed, as demonstrated in scripts/generate-large-graph.mjs.

Manage File Size and Security

For very large projects, avoid committing massive JSON files to keep repository size manageable; use static hosting instead. Additionally, the knowledge graph may contain internal source code identifiers, so ensure you only share it within trusted team boundaries or secure networks.

Summary

• The Egonex-AI knowledge graph is stored in .understand-anything/knowledge-graph.json and copied to packages/dashboard/public/knowledge-graph.json
• Share the graph by committing to version control, serving via HTTP, direct file transfer, dashboard bundling, or CI/CD artifacts
• Use the dashboard's public copy to guarantee UI compatibility when sharing visualizations
• Keep outputs deterministic and secure sensitive identifiers when distributing to teams

Frequently Asked Questions

Where exactly is the knowledge graph file generated?

The primary file is written to .understand-anything/knowledge-graph.json in your project root after the analysis pipeline finishes. A duplicate is placed in packages/dashboard/public/knowledge-graph.json specifically for the dashboard UI consumption.

Can I view the knowledge graph without sharing the JSON file?

Yes, you can run the dashboard locally using the copy in packages/dashboard/public/, but to share the visualization with teammates, you must distribute the underlying JSON file or host it on a shared endpoint that the UI can access.

Is it safe to commit the knowledge-graph.json to a public repository?

Exercise caution when sharing the Egonex-AI knowledge graph publicly, as the JSON may contain internal source code identifiers, file paths, and function names that reveal implementation details about your codebase. Only commit the file to private repositories or secure team environments.

How do I automate knowledge graph sharing in CI/CD?

Add a step to your pipeline that runs the analysis command, then use your platform's artifact upload action (such as actions/upload-artifact@v3 for GitHub Actions) to store the JSON. Downstream jobs can retrieve this artifact for documentation builds, testing, or further analysis workflows.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}