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skene-growth CLI documentation

Analyze codebases for product-led growth opportunities, generate growth plans, and build implementation prompts.

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Quickstart

Get from zero to a full growth plan in five commands.

Prerequisites

  • Python 3.11 or later
  • uv installed (curl -LsSf https://astral.sh/uv/install.sh | sh)
  • An API key from OpenAI, Google Gemini, or Anthropic -- OR a local LLM running via LM Studio or Ollama

The 5-step workflow

Step 1: Create a config file

uvx skene-growth config --init

This creates .skene-growth.config in your current directory with sensible defaults. The file is created with restrictive permissions (0600 on Unix) since it will hold your API key.

Step 2: Configure your LLM provider

uvx skene-growth config

This shows your current configuration, then asks if you want to edit it. If you choose to edit, an interactive setup walks you through:

  1. Provider -- choose from openai, gemini, anthropic, lmstudio, ollama, or generic (any OpenAI-compatible endpoint)
  2. Model -- pick from a curated list per provider, or enter a custom model name
  3. Base URL -- only prompted if you select the generic provider
  4. API key -- entered as a password field (hidden input)

The configuration is saved back to your .skene-growth.config file.

Tip: You can skip this step entirely by passing --api-key and --provider flags directly to each command, or by setting the SKENE_API_KEY and SKENE_PROVIDER environment variables.

Step 3: Analyze your codebase

uvx skene-growth analyze .

This scans your codebase and generates two files in ./skene-context/:

  • growth-manifest.json -- structured data about your tech stack, existing growth features, and growth opportunities
  • growth-template.json -- a business-type-aware growth template with prioritized recommendations

The analysis uses your configured LLM to understand your codebase structure, detect the technology stack (framework, language, database, hosting), identify existing growth features, and surface new growth opportunities.

You can pass a different path instead of . to analyze a project elsewhere on disk:

uvx skene-growth analyze /path/to/your/project

Step 4: Generate a growth plan

uvx skene-growth plan

This reads growth-manifest.json and growth-template.json from ./skene-context/ (auto-detected) and generates a growth-plan.md file in the same directory.

The plan is produced by a "Council of Growth Engineers" analysis -- multiple specialized perspectives evaluate your codebase and converge on a prioritized growth strategy. The output includes:

  • An executive summary
  • Prioritized growth opportunities with implementation details
  • A technical execution section with the recommended "next build"
  • An implementation todo list

For onboarding-focused analysis instead of general growth, add the --onboarding flag:

uvx skene-growth plan --onboarding

Step 5: Build an implementation prompt

uvx skene-growth build

This command:

  1. Reads growth-plan.md from ./skene-context/ (auto-detected)
  2. Extracts the Technical Execution section (the recommended next build, exact logic, data triggers, sequence)
  3. Uses your LLM to generate a focused implementation prompt
  4. Asks where you want to send it:
    • Cursor -- opens via deep link
    • Claude -- launches in terminal
    • Show -- prints the full prompt to the terminal

The prompt is also saved to a file in ./skene-context/ for later use.

What you get

After running all five steps, your ./skene-context/ directory contains:

FileDescription
growth-manifest.jsonStructured analysis of your codebase: tech stack, current growth features, opportunities
growth-template.jsonBusiness-type-aware growth template with prioritized recommendations
growth-plan.mdFull growth plan with executive summary, priorities, and technical execution details
implementation-prompt.mdReady-to-use prompt for your AI coding assistant

Alternative: Quick one-liner

If you want to try the analysis without setting up a config file first, pass your API key inline:

uvx skene-growth analyze . --api-key "your-key"

This uses the default provider (openai) and model (gpt-4o). To use a different provider:

uvx skene-growth analyze . --api-key "your-key" --provider gemini --model gemini-3-flash-preview

Alternative: Free audit (no API key)

If you want to see what skene-growth does before configuring an LLM, the audit command runs a local preview with no API key required:

uvx skene-growth audit .

This shows a sample growth analysis report demonstrating the kind of strategic insights available with full API-powered analysis. It does not require any API key or LLM configuration.

Next steps