Skene

Skene reads your codebase and produces a user journey for your product: the lifecycle stages a user moves through, the milestones inside each stage, and the code or database evidence that proves each milestone is real.

Quick Start

Install and launch the interactive terminal UI:

curl -fsSL https://raw.githubusercontent.com/SkeneTechnologies/skene/main/tui/install.sh | bash
skene

The wizard walks you through provider selection, authentication, and analysis — no configuration needed upfront.

What It Does

Skene turns a repository into a single journey.yaml describing your product's user lifecycle, and renders it as an interactive diagram.

• Agentic analysis — two parallel agents read your project: one walks the codebase, one walks your SQL schemas. They each propose candidate milestones, which are then merged and classified into a canonical seven-stage lifecycle.
• Seven-stage user journey — every product maps to the same canonical stages (discovery, onboarding, activation, engagement, retention, expansion, virality) so journeys are comparable across products. Stage names are specialized to your product where useful.
• Evidence-backed milestones — each milestone carries a tracked_event, a confidence score, and one or more evidence chips pointing back to the exact code path, database table, or config file that justifies it.
• Journey visualizer — the TUI opens a local web app that lays out the stages as columns, with milestone cards and clickable evidence chips, so you can review the journey alongside the underlying source.
• Code-only, schema-only, or both — run against just a codebase, just a directory of *.sql files, or both for richer evidence.

Supports OpenAI, Gemini, Claude, LM Studio, Ollama, and any OpenAI-compatible endpoint.

Installation

Terminal UI (recommended)

The TUI is an interactive wizard that guides you through the entire workflow. No prerequisites — the installer handles everything.

# Install the TUI
curl -fsSL https://raw.githubusercontent.com/SkeneTechnologies/skene/main/tui/install.sh | bash

# Launch it
skene

Python CLI

If you prefer the command line, you can run Skene directly with uvx (no install needed) or install it globally:

# Install uv (if you don't have it)
curl -LsSf https://astral.sh/uv/install.sh | sh

# Run directly (no install needed)
uvx skene analyse-journey .

# Or install globally
pip install skene
skene analyse-journey .

Useful flags:

• --schema-dir <dir> — point at a directory of exported *.sql files to enable the schema agent
• -o <path> — override the output file (default ./skene-context/journey.yaml)
• --no-specialize — keep the canonical stage names instead of letting the LLM specialize them

For f

... View full README on GitHub