latexnav: Python Tool for LLM and Human Navigation of LaTeX Files

latexnav is a free open source Python tool designed to help LLMs and humans navigate LaTeX files by parsing structural elements and providing summaries with line numbers.
Key Features and Functionality
The tool parses LaTeX files to extract:
- Theorems
- Definitions
- Sections
- Labels
- Cross-references
- Dependencies
It produces structural summaries with authoritative line numbers, which helps save time and tokens while managing context.
Problem It Solves for AI Agents
When AI agents (Claude, GPT, Gemini, etc.) work with large LaTeX manuscripts via CLI tools like Claude Code, Codex, or OpenCode:
- Reading raw .tex files can consume thousands of context tokens
- Agents lack structural awareness of what theorems exist, what depends on what, or where proofs start
latexnav provides agents with structural navigation capabilities:
- View a theorem statement in 3 lines instead of reading a 200-line file
- Check reverse dependencies before modifying a result
- Get a compact overview of an entire chapter
- Know exactly where to start reading via provided line numbers
Development and Integration
The tool was written by Claude inside Claude Code, with Claude playing a significant role in UX testing and feature development. The developer periodically asked agents about the tool to get suggestions for improvements and new features.
Installation is straightforward:
pip install latexnavTo integrate into a CLI tool like Claude Code, tell the agent to read the README file in the git repository and set up its memory/instructions files as suggested in the LLM agent integration section.
The tool is available on GitHub at https://github.com/drwoood/latexnav.
📖 Read the full source: r/ClaudeAI
👀 See Also

Self-Maintaining Documentation System Using Fenced Blocks for Zero Drift
A developer built a bash script that extracts structured data directly from source files and injects it into CLAUDE.md through fenced HTML comment blocks, ensuring documentation stays in sync with code without manual maintenance.

One-Command Docker Setup for OpenClaw with Full-Disk Encryption and Monitoring
A Docker setup for OpenClaw that provides full-disk encryption guides, Tini as PID 1, built-in monitoring tools, and data stored as plain files on the host. Deployment requires just two commands: git clone and ./shell.

Steelman R5: Fine-tuned 14B Model Outperforms Claude Opus on Ada Code Generation
A developer fine-tuned Qwen2.5-Coder-14B-Instruct using QLoRA on a compiler-verified dataset of 3,430 Ada/SPARK instruction pairs, achieving 68.6% compilation rate on a custom benchmark versus Claude Opus 4.6's 42.1%. The model is available via Ollama and fits in 12GB VRAM.

CodeVibe: Push Notifications for AI Coding Agents When Blocked on Input
CodeVibe sends push notifications to your phone when AI coding agents like Claude Code get stuck waiting for approval on edit operations. You can review file diffs and respond with numbered options to keep the agent moving.