ReadMenator

A token-free, offline, production-grade polyglot codebase knowledge graph & architectural analyzer.

No LLMs. No tokens. No cloud costs. Pure static analysis via AST + regex.

ReadMenator builds production-grade codebase knowledge graphs and architectural health reports 100% offline. Identify structural risks, security flaws, and change impact patterns instantly across 19 languages.

• https://pypi.org/project/readmenator/

Supported Languages (19)

C, C++, Python, Go, Rust, JavaScript, TypeScript, Java, C#, Shell, PHP, Dart, GDScript, Nim, Assembly, Ruby, Swift, Kotlin, Scala, Lua, Elixir.

What ReadMenator Does Better Than Graphify

Installation

pip install readmenator 

or install from path

pip install .

Usage

Generate knowledge base

python -m readmenator /path/to/project --rebuild

Creates KNOWLEDGE_BASE.md with Table of Contents, Statistics Dashboard, Architectural Layers, God Nodes, Community Analysis, Surprising Connections, Suggested Questions, Mermaid graph (internal edges + community subgraphs), and Architecture Reference.

Export formats

python -m readmenator /path/to/project --export-all     # JSON + HTML + SVG
python -m readmenator /path/to/project --json           # graph.json (GraphRAG-ready)
python -m readmenator /path/to/project --html           # graph.html (interactive vis.js)
python -m readmenator /path/to/project --svg            # graph.svg (static)
python -m readmenator /path/to/project --graphml        # graph.graphml (Gephi/yEd)
python -m readmenator /path/to/project obsidian         # Obsidian vault (wikilinks)

Query, explain, and path trace

python -m readmenator /path/to/project query "What classes handle HTTP?"
python -m readmenator /path/to/project explain Database
python -m readmenator /path/to/project path SymbolA SymbolB

Analysis

python -m readmenator /path/to/project analyze          # community + god nodes + questions
python -m readmenator /path/to/project layers           # architectural layer detection

Advanced Architectural Insights (Out of the Box)

ReadMenator goes beyond simple visualization. It runs complex graph algorithms locally to give you deep insights into your code's health:

• Change Impact Analysis: Know exactly which files are highly coupled. ReadMenator calculates direct and transitive dependents so you can predict what will break before you refactor.
• Hotspot Detection: Automatically ranks files by combining cognitive complexity (symbol richness) and graph centrality to pinpoint technical debt.
• Taint Propagation Mapping: Traces how risky imports (like subprocess or OS-level sinks) propagate transitively through your codebase dependency graph.
• Community & Layer Detection: Automatically groups files into structural layers (utility, business logic, infrastructure) and highly cohesive communities using label propagation.

Automation

python -m readmenator /path/to/project update           # incremental (SHA256 cache)
python -m readmenator /path/to/project watch            # auto-rebuild on file changes
python -m readmenator /path/to/project analyze          # Analyze the proyect

Run tests

python -m readmenator --test

Architecture

Security

• Symlinks rejected
• File size capped at 10 MB
• Directory depth limited to 20
• No absolute paths in source code
• No external network calls in any module
• All exceptions silently caught during parsing

License

AGPL-3.0