Luminos

A file system intelligence tool. Scans a directory and produces a reconnaissance report that tells you what the directory is, what's in it, and what might be worth your attention.

Luminos has two modes. The base mode is a single Python file that uses only the standard library and GNU coreutils. No pip install, no virtual environment, no dependencies to audit. The --ai mode runs a multi-pass agentic investigation against the Claude API to reason about what the project actually does and flag anything that looks off. AI mode is opt-in and is the only path that requires pip-installable packages.

Why

Most "repo explorer" tools answer one question: "what files are here?" Luminos is built around a harder question: "what is this, and should I be worried about any of it?"

The base scan gives you the mechanical answer: directory tree, file classification across seven categories, language breakdown with line counts, recently modified files, disk usage, and the largest files. That is usually enough for a quick "what is this" look.

The AI mode goes further. It runs an isolated investigation per directory, leaves-first, with a small toolbelt (read files, run whitelisted coreutils commands, write cache entries) and a per-directory context budget. Each directory gets its own summary, and a final synthesis pass reads only the directory-level cache entries to produce a whole-project verdict. Findings are flagged with a severity level (critical, concern, or info) so the important stuff floats to the top.

Features

• Zero dependencies in base mode. Runs on bare Python 3 plus the GNU coreutils you already have.
• Graceful degradation everywhere. Permission denied, subprocess timeouts, missing API key, missing optional packages: all handled without crashing the scan.
• Directory tree. Visual tree with configurable depth and exclude patterns.
• File classification. Files bucketed into seven categories (code, config, docs, data, media, binary, other) via file(1) magic.
• Language detection and LOC counting. Which languages are present, how many lines of code per language.
• Recently modified files. Surface the files most likely to reflect current activity.
• Disk usage. Per-directory disk usage with top offenders called out.
• Watch mode. Re-scan every 30 seconds and show diffs.
• JSON output. Pipe reports to other tools or save for comparison.
• AI investigation (opt-in). Multi-pass, leaves-first agentic analysis via Claude, with an investigation cache so repeat runs are cheap.
• Severity-ranked flags. Findings are sorted so critical items are the first thing you see.

Installation

Base mode

No installation required. Clone and run.

git clone https://github.com/archeious/luminos.git
cd luminos
python3 luminos.py <target>

Works on any system with Python 3 and standard GNU coreutils (wc, file, grep, head, tail, stat, du, find).

AI mode

AI mode needs a few pip-installable packages. The project ships a helper script that creates a dedicated virtual environment and installs them:

./setup_env.sh
source ~/luminos-env/bin/activate

The packages installed are anthropic, tree-sitter, a handful of tree-sitter language grammars, and python-magic.

You also need an Anthropic API key exported as an environment variable:

export ANTHROPIC_API_KEY=your-key-here

Check which optional dependencies are present:

python3 luminos.py --install-extras

Usage

Base scan

python3 luminos.py /path/to/project

AI scan

python3 luminos.py --ai /path/to/project

Common flags

# Deeper tree, include hidden files, exclude build and vendor dirs
python3 luminos.py -d 8 -a -x .git -x node_modules -x vendor /path/to/project

# JSON output to a file
python3 luminos.py --json -o report.json /path/to/project

# Watch mode (re-scan every 30s, show diffs)
python3 luminos.py --watch /path/to/project

# Force a fresh AI investigation, ignoring the cache
python3 luminos.py --ai --fresh /path/to/project

# Clear the AI investigation cache
python3 luminos.py --clear-cache

Run python3 luminos.py --help for the full flag list.

How AI mode works

A short version of what happens when you pass --ai:

1. Discover every directory under the target.
2. Sort leaves-first so the deepest directories are investigated before their parents.
3. Run an isolated agent loop per directory with a max of 10 turns each. The agent has a small toolbelt: read files, run whitelisted coreutils commands (wc, file, grep, head, tail, stat, du, find), and write cache entries.
4. Cache everything. Each file and directory summary is written to /tmp/luminos/ so that subsequent runs on the same target don't burn tokens re-deriving things that haven't changed.
5. Context budget guard. Per-turn input_tokens is watched against a budget (currently 70% of the model's context window) so a rogue directory can't blow the context and silently degrade quality.
6. Final synthesis pass reads only the directory-level cache entries (not the raw files) to produce a project-level summary and the severity-ranked flags.

Development

Run the test suite:

python3 -m unittest discover -s tests/

Modules that are intentionally not unit tested and why:

• luminos_lib/ai.py: requires a live Anthropic API, tested in practice
• luminos_lib/ast_parser.py: requires tree-sitter grammars installed
• luminos_lib/watch.py: stateful event loop, tested manually
• luminos_lib/prompts.py: string templates only

License

Apache License 2.0. See LICENSE for the full text.

Source of truth

The canonical home for this project is the Forgejo repository. The GitHub copy is a read-only mirror, pushed automatically from Forgejo. Issues, pull requests, and the project wiki live on Forgejo.