CLI Reference
Complete reference for every skene command and flag.
For in-depth usage of individual commands, see the guides. This page is a lookup reference.
Global Options
| Flag | Description |
|---|---|
--version, -V | Show version and exit |
--help | Show help message and exit |
When invoked with no arguments, skene prints help and exits. The shorthand skene (without -growth) defaults to the chat command instead.
analyze
Analyze a codebase and generate growth-manifest.json.
Scans your codebase to detect the technology stack, current growth features, and new growth opportunities. Requires an LLM provider (or falls back to a sample preview if no API key is set).
skene analyze [PATH] [OPTIONS]
Arguments
| Argument | Default | Description |
|---|---|---|
PATH | . | Path to codebase directory to analyze (must exist) |
Options
| Flag | Short | Default | Description |
|---|---|---|---|
--output PATH | -o | ./skene-context/growth-manifest.json | Output path for the manifest file. If a directory is given, growth-manifest.json is appended automatically. |
--api-key TEXT | $SKENE_API_KEY or config | API key for the LLM provider | |
--provider TEXT | -p | config value | LLM provider: openai, gemini, anthropic (or claude), lmstudio, ollama, generic (aliases: openai-compatible, openai_compatible) |
--model TEXT | -m | provider default | LLM model name (e.g. gpt-4o, gemini-3-flash-preview) |
--base-url TEXT | $SKENE_BASE_URL or config | Base URL for OpenAI-compatible API endpoint. Required when provider is generic. | |
--verbose | -v | false | Enable verbose output |
--product-docs | false | Also generate product-docs.md with user-facing feature documentation | |
--features | false | Only analyze growth features and update feature-registry.json (skips opportunities and revenue leakage) | |
--exclude TEXT | -e | config value | Folder names to exclude from analysis. Repeatable: --exclude tests --exclude vendor. Merged with exclude_folders from config. |
--debug | false | Log all LLM input/output to .skene/debug/ | |
--no-fallback | false | Disable model fallback on rate limits (429). Retries the same model with exponential backoff instead of switching to a cheaper model. |
Behavior notes
- When no API key is provided and the provider is not local (
lmstudio,ollama,generic), the command falls back to a sample preview. - Local providers (
lmstudio,ollama,generic) do not require an API key. - The
genericprovider requires--base-url.
See the analyze guide for detailed usage.
plan
Generate a growth plan using the Council of Growth Engineers methodology.
Reads the manifest and template produced by analyze, then uses an LLM to create a prioritized growth plan with implementation tasks.
skene plan [OPTIONS]
Options
| Flag | Short | Default | Description |
|---|---|---|---|
--manifest PATH | auto-detected | Path to growth-manifest.json. Auto-detected from ./skene-context/, ./, or the context directory. | |
--template PATH | auto-detected | Path to growth-template.json. Auto-detected using the same search order. | |
--context PATH | -c | auto-detected | Directory containing manifest and template files. Checked before default paths. |
--output PATH | -o | ./skene-context/growth-plan.md | Output path for the growth plan (markdown). If a directory is given, growth-plan.md is appended. |
--api-key TEXT | $SKENE_API_KEY or config | API key for the LLM provider | |
--provider TEXT | -p | config value | LLM provider: openai, gemini, anthropic/claude, lmstudio, ollama, generic |
--model TEXT | -m | provider default | LLM model name |
--base-url TEXT | $SKENE_BASE_URL or config | Base URL for OpenAI-compatible API endpoint. Required when provider is generic. | |
--verbose | -v | false | Enable verbose output |
--activation | false | Generate an activation-focused plan using a Senior Activation Engineer perspective | |
--prompt TEXT | Additional user prompt to influence the plan generation | ||
--debug | false | Log all LLM input/output to .skene/debug/ | |
--no-fallback | false | Disable model fallback on rate limits (429). Retries the same model with exponential backoff instead of switching to a cheaper model. |
Auto-detection order
Both --manifest and --template are auto-detected by searching these paths in order:
<context>/growth-manifest.json(if--contextis set)./skene-context/growth-manifest.json./growth-manifest.json
Neither file is strictly required; the plan command works with whatever context is available.
See the plan guide for detailed usage.
build
Build an AI-ready implementation prompt from your growth plan, then choose where to send it.
Extracts the Technical Execution section from the growth plan, uses an LLM to generate a focused implementation prompt, and offers interactive delivery options (Cursor deep link, Claude CLI, or display).
skene build [OPTIONS]
Options
| Flag | Short | Default | Description |
|---|---|---|---|
--plan PATH | auto-detected | Path to the growth plan markdown file. Auto-detected from ./skene-context/growth-plan.md or ./growth-plan.md. | |
--context PATH | -c | auto-detected | Directory containing growth-plan.md |
--api-key TEXT | $SKENE_API_KEY or config | API key for the LLM provider | |
--provider TEXT | -p | config value | LLM provider: openai, gemini, anthropic/claude, lmstudio, ollama, generic |
--model TEXT | -m | provider default | LLM model name |
--base-url TEXT | $SKENE_BASE_URL or config | Base URL for OpenAI-compatible API endpoint. Required when provider is generic. | |
--debug | false | Log all LLM input/output to .skene/debug/ | |
--no-fallback | false | Disable model fallback on rate limits (429). Retries the same model with exponential backoff instead of switching to a cheaper model. | |
--target TEXT | -t | interactive | Skip the interactive menu and send the prompt directly. Options: cursor, claude, show, file. |
--feature TEXT | -f | Bias toward this feature name when linking the growth loop to a feature in the registry |
Delivery targets
After generating the prompt, an interactive menu asks where to send it:
- Cursor -- opens the prompt via a Cursor deep link
- Claude -- launches the Claude CLI with the prompt file
- Show -- prints the full prompt to the terminal
When --target is provided, the interactive menu is skipped entirely. The file target saves the prompt to disk and exits without opening any editor or printing the full content. This is the recommended mode for scripting and subprocess usage.
The prompt is always saved to a file in the plan's parent directory regardless of target selection.
Behavior notes
- Requires a configured LLM (API key + provider). Falls back to a template-based prompt if the LLM call fails.
- Also generates and saves a growth loop definition JSON alongside the prompt.
- Use
--target filefor non-interactive pipelines (e.g.analyze && plan && build --target file).
See the build guide for detailed usage.
status
Show implementation status of growth loop requirements.
Loads all growth loop JSON definitions from skene-context/growth-loops/ and uses AST parsing to verify that required files, functions, and patterns are implemented. Displays a report showing which requirements are met and which are missing.
skene status [PATH] [OPTIONS]
Arguments
| Argument | Default | Description |
|---|---|---|
PATH | . | Path to the project root directory (must exist) |
Options
| Flag | Short | Default | Description |
|---|---|---|---|
--context PATH | -c | auto-detected | Path to skene-context directory. Auto-detected from <PATH>/skene-context/ or ./skene-context/. |
--find-alternatives | false | Use LLM to search for existing functions that might fulfill missing requirements | |
--api-key TEXT | $SKENE_API_KEY or config | API key for the LLM provider. Required when --find-alternatives is set. | |
--provider TEXT | -p | config value | LLM provider: openai, gemini, anthropic, ollama |
--model TEXT | -m | provider default | LLM model name |
Context auto-detection
When --context is not specified, the command checks these paths in order:
<PATH>/skene-context/(wherePATHis the positional argument)./skene-context/
The directory must contain a growth-loops/ subdirectory with at least one JSON file.
Behavior notes
- Validates every growth loop JSON file found in
<context>/growth-loops/. - Uses Python AST parsing to verify function and class definitions, import statements, and content patterns.
- With
--find-alternatives, extracts all functions from the codebase and uses the LLM to find semantic matches for missing requirements (confidence threshold: 60%). - Does not require an API key unless
--find-alternativesis enabled.
See the status guide for detailed usage.
chat
Interactive terminal chat with access to skene analysis tools.
skene chat [PATH] [OPTIONS]
Arguments
| Argument | Default | Description |
|---|---|---|
PATH | . | Path to codebase directory |
Options
| Flag | Short | Default | Description |
|---|---|---|---|
--api-key TEXT | $SKENE_API_KEY or config | API key for the LLM provider | |
--provider TEXT | -p | config value | LLM provider: openai, gemini, anthropic/claude, lmstudio, ollama, generic |
--model TEXT | -m | provider default | LLM model name |
--base-url TEXT | $SKENE_BASE_URL or config | Base URL for OpenAI-compatible API endpoint. Required when provider is generic. | |
--max-steps INT | 4 | Maximum number of tool calls the LLM can make per user request | |
--tool-output-limit INT | 4000 | Maximum characters of tool output kept in conversation context | |
--debug | false | Log all LLM input/output to .skene/debug/ |
Behavior notes
- When using the
skeneshorthand (notskene), running without a subcommand defaults tochat. - Requires an API key unless using a local provider.
See the chat guide for detailed usage.
validate
Validate a growth-manifest.json file against the GrowthManifest schema.
skene validate MANIFEST
Arguments
| Argument | Required | Description |
|---|---|---|
MANIFEST | Yes | Path to the growth-manifest.json file to validate (must exist) |
Behavior notes
- Parses the file as JSON, then validates it against the Pydantic
GrowthManifestmodel. - On success, prints a summary table showing project name, version, tech stack, and feature counts.
- On failure, prints the validation error and exits with code 1.
config
Manage skene configuration files.
skene config [OPTIONS]
Options
| Flag | Default | Description |
|---|---|---|
--init | false | Create a sample .skene.config file in the current directory |
--show | false | Show current configuration values and exit (no interactive editing) |
Default behavior (no flags)
When invoked without --init or --show:
- Displays current configuration values (same as
--show) - Asks whether you want to edit the configuration
- If yes, launches an interactive setup flow to select provider, model, and enter an API key
Configuration load order
Configuration is resolved in this order (later sources override earlier ones):
- User config:
~/.config/skene/config - Project config:
./.skene.config - Environment variables:
SKENE_API_KEY,SKENE_PROVIDER - CLI flags
See the configuration guide for file format and all supported options.
push
Build Supabase migrations from growth loop telemetry and push artifacts to upstream.
Creates idempotent trigger-based migrations that INSERT into event_log for each telemetry-defined table. Optionally pushes growth loops and telemetry SQL to Skene Cloud upstream.
skene push [PATH] [OPTIONS]
Arguments
| Argument | Default | Description |
|---|---|---|
PATH | . | Project root (output directory for supabase/) |
Options
| Flag | Short | Default | Description |
|---|---|---|---|
--context PATH | -c | auto-detected | Path to skene-context directory. Auto-detected from <PATH>/skene-context/ or ./skene-context/. |
--loop TEXT | -l | Push only this loop (by loop_id). If omitted, pushes all loops with Supabase telemetry. | |
--upstream TEXT | -u | config | Upstream workspace URL (e.g. https://skene.ai/workspace/my-app). Resolved from .skene.config or this flag. |
--push-only | false | Re-push current output without regenerating migrations |
Behavior notes
- Requires growth loops with Supabase telemetry (type
"supabase") inskene-context/growth-loops/. - Generates a migration file at
supabase/migrations/<timestamp>_skene_telemetry.sql. - When
--upstreamis provided (or resolved from.skene.config), pushes the package (growth loops + telemetry SQL) to the upstream API. - Use
skene loginto authenticate before pushing to upstream.
See the push guide for detailed usage.
login
Log in to Skene Cloud upstream for push.
skene login [OPTIONS]
Options
| Flag | Short | Default | Description |
|---|---|---|---|
--upstream TEXT | -u | Upstream workspace URL (e.g. https://skene.ai/workspace/my-app) | |
--status | -s | false | Show current login status for this project |
Behavior notes
- Saves upstream URL, workspace, and API key to
.skene.configwith restrictive permissions (0600). - Use
--statusto check whether you are logged in for the current project.
See the login guide for detailed usage.
logout
Log out from upstream (remove saved token).
skene logout
Behavior notes
- Removes upstream credentials from
.skene.config. - Does not invalidate the token server-side.
init
Create the skene base schema migration for Supabase.
skene init [PATH]
Arguments
| Argument | Default | Description |
|---|---|---|
PATH | . | Project root (output directory for supabase/) |
Behavior notes
- Writes
supabase/migrations/20260201000000_skene_schema.sqlcontaining the base schema:event_log,failed_events,enrichment_maptables and supporting functions. - Safe to run repeatedly -- skips if the migration already exists.
- Run
supabase db pushafter to apply the migration.
features
Manage the growth feature registry.
features export
Export the feature registry for use in external tools.
skene features export [PATH] [OPTIONS]
Arguments
| Argument | Default | Description |
|---|---|---|
PATH | . | Project root (to locate skene-context) |
Options
| Flag | Short | Default | Description |
|---|---|---|---|
--context PATH | -c | auto-detected | Path to skene-context directory |
--format TEXT | -f | json | Output format: json, csv, markdown |
--output PATH | -o | stdout | Output file path. Prints to stdout if omitted. |
Behavior notes
- Reads
feature-registry.jsonfrom the context directory. - Requires running
analyzefirst to populate the registry. - Use for integrating with dashboards, Linear, Notion, or documentation.
See the features guide for detailed usage.
generate (deprecated)
This command is deprecated and will be removed. Use analyze --product-docs instead.
skene generate [OPTIONS]
| Flag | Short | Description |
|---|---|---|
--manifest PATH | -m | Path to growth-manifest.json |
--output PATH | -o | Output directory (default: ./skene-docs) |
The command prints a deprecation warning and exits with code 1.
Environment Variables
| Variable | Used by | Description |
|---|---|---|
SKENE_API_KEY | analyze, plan, build, chat, status | API key for the LLM provider. Equivalent to --api-key. |
SKENE_BASE_URL | analyze, plan, build, chat | Base URL for OpenAI-compatible endpoints. Equivalent to --base-url. |
SKENE_PROVIDER | config loading | LLM provider override at the environment level. |
SKENE_UPSTREAM_API_KEY | push, login | API key for upstream authentication. |
SKENE_DEBUG | all commands | Enable debug mode (true/false). |
Exit Codes
| Code | Meaning |
|---|---|
0 | Success |
1 | Error (invalid input, missing API key, validation failure, or deprecated command) |
Examples
# Full workflow
uvx skene config --init
uvx skene config
uvx skene analyze .
uvx skene plan
uvx skene build
# Analyze with explicit provider settings
uvx skene analyze ./my-app -p gemini -m gemini-3-flash-preview --api-key "YOUR_KEY"
# Analyze with a local LLM (no API key needed)
uvx skene analyze . -p ollama -m llama3
# Analyze with OpenAI-compatible endpoint
uvx skene analyze . -p generic --base-url http://localhost:8080/v1
# Generate activation-focused plan
uvx skene plan --activation
# Validate a manifest
uvx skene validate ./skene-context/growth-manifest.json
# Interactive chat
uvx skene chat . -p openai -m gpt-4o
# Check growth loop implementation status
uvx skene status
# Check status with LLM-powered alternative matching
uvx skene status --find-alternatives --api-key "YOUR_KEY"
# Features-only analysis (updates feature registry without full analysis)
uvx skene analyze . --features
# Push growth loops to Supabase + upstream
uvx skene push
uvx skene push --upstream https://skene.ai/workspace/my-app
uvx skene push --loop my_loop_id
# Login/logout from upstream
uvx skene login --upstream https://skene.ai/workspace/my-app
uvx skene login --status
uvx skene logout
# Initialize Supabase base schema
uvx skene init
# Export feature registry
uvx skene features export --format markdown -o features.md
# Quick preview (no API key, just run analyze without a key)
uvx skene analyze .