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Build navigable codebase knowledge graphs with Understand Anythi

Turn a repository or wiki into an interactive knowledge graph that agents and humans can search, explore, and query before implementation work.

What is Build navigable codebase knowledge graphs with Understand Anythi?

Build navigable codebase knowledge graphs with Understand Anythi is a Claude Code agent skill that turn a repository or wiki into an interactive knowledge graph that agents and humans can search, explore, and query before implementation work.

Works with✓Claude Code✓Codex CLI✓Cursor✓Gemini CLI✓OpenCode
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From the skill README

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Documentation

Build navigable codebase knowledge graphs with Understand Anything

Turn a repository or wiki into an interactive knowledge graph that agents and humans can search, explore, and query before implementation work.

Prerequisites

Understand Anything plugin or installer, supported coding harness such as Claude Code, Codex, OpenCode, Gemini CLI, Cursor, or related agent CLI, target repository or knowledge base

Installation

Requirements and caveats from upstream:

  • Navigate your codebase as an interactive knowledge graph — every file, function, and class is a node you can click, search, and explore. Select any node to see plain-English summaries, relationships, and guided tours.

Basic usage or getting-started notes:

Documentation

Source

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

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Add graph-backed memory and context retrieval to agent workflows

Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.

Add IDE-style semantic code navigation and symbol-safe refactors

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Add persistent project memory and hook-driven synthesis with Cla

Keep Claude Code sessions grounded in prior decisions, project context, and daily handoff notes instead of starting from zero every time.

Add Postgres-native vector retrieval to agent and RAG workflows

Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.

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Add temporal context memory to agent workflows with Zep

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