Generate an interactive knowledge graph from a codebase with an agent

Instead of reading code or docs linearly, developers point an agent at a repository and have it build an interactive knowledge graph that can be searched, browsed, and queried with natural language questions. This turns static codebases into a navigable map of relationships, used for faster onboarding and code comprehension.

What it is

This move turns a repository into a browsable, queryable graph instead of leaving a new contributor to read files top to bottom. An agent plugin, such as Understand Anything, scans the codebase and related files to build a graph of components, dependencies, and relationships, then layers on an interactive interface for exploring it. Beyond raw structure, the tool can also map code to business concepts like authentication flows, payment pipelines, or user lifecycles, so the graph explains what the system does, not just how files connect.

How to do it

• Install the plugin into your agent environment, for example with a plugin marketplace command inside Claude Code, then add and install the understand-anything package.
• The same workflow also works with Codex, OpenCode, and Gemini CLI.
• Run the generation command (such as /understand) against your repository to build the graph.
• Use the interactive dashboard to drill down hierarchically, apply fuzzy or semantic search, and filter nodes by type, complexity, or layer.
• Switch into business knowledge mode to see domain groupings like auth flow or session management instead of a plain file and function graph.
• Use the dependency path finder to trace the shortest route between two components when you need to understand how two parts of the system are linked.
• Export the graph as PNG, SVG, or filtered JSON to drop into documentation, onboarding materials, or presentations.
• Generate an AI walkthrough or guided tour that steps through the codebase so newcomers get a narrated introduction rather than a blank graph.

When it helps

This is most useful when onboarding someone onto an unfamiliar codebase, when you need a shared map for a team that spans many file types such as Dockerfiles, Terraform, SQL, and Markdown, or when you want a quick way to communicate how a specific flow works without walking someone through raw source line by line.

Pitfalls

A graph that only shows files, functions, and edges can end up as an unreadable tangle with no explanatory value. Make sure you are using the business or domain view, not just the raw structural one, if your goal is comprehension rather than a dependency diagram.

Sources

• Egonex-AI/Understand-Anything - GitHub