Skene
Product
Pricing
Docs
Blog
Events
About
Log InStart free
ProductPricingDocsBlogEventsAbout
Log InStart free
Skene subpage background texture

From an earlier version of Skene. See the current product →

  1. Home
  2. /
  3. Resources
  4. /
  5. Docs
  6. /
  7. skene CLI
CLI docs

Troubleshooting

Navigation

skene CLI

  • Quickstart
  • Overview
  • Installation
  • Push
  • Login
  • Status
  • Features
  • LLM Providers
  • Configuration
  • MCP Server
  • CLI Reference
  • HTTP API
  • Python API
  • Troubleshooting

Resources

  • Skene Cloud docs
  • Playbooks
  • Glossary

skene CLI

  • Quickstart
  • Overview
  • Installation
  • Push
  • Login
  • Status
  • Features
  • LLM Providers
  • Configuration
  • MCP Server
  • CLI Reference
  • HTTP API
  • Python API
  • Troubleshooting

Resources

  • Skene Cloud docs
  • Playbooks
  • Glossary

Solutions for common issues when using skene.

LM Studio

Context length error

Error code: 400 - {'error': 'The number of tokens to keep from the initial prompt is greater than the context length...'}

The model's context length is too small for the analysis. To fix:

  1. In LM Studio, unload the current model
  2. Go to Developer > Load
  3. Click on Context Length: Model supports up to N tokens
  4. Set it to the maximum supported value
  5. Reload to apply changes

Reference: lmstudio-ai/lmstudio-bug-tracker#237

Connection refused

Ensure:

  • LM Studio is running
  • A model is loaded and ready
  • The server is running on the default port (http://localhost:1234)

For a custom port:

export LMSTUDIO_BASE_URL="http://localhost:8080/v1"

Ollama

Connection refused

Ensure:

  • Ollama is running (ollama serve)
  • A model is pulled and available (ollama list)
  • The server is on the default port (http://localhost:11434)

Getting started with Ollama:

# Pull a model
ollama pull llama3.3

# Start the server (usually runs automatically after install)
ollama serve

For a custom port:

export OLLAMA_BASE_URL="http://localhost:8080/v1"

API key issues

Missing API key

In local (embedded) mode, analyse-journey requires a configured LLM. Cloud providers need an API key; local providers (lmstudio, ollama, generic) do not. Set your key using one of:

# CLI flag
uvx skene analyse-journey . --api-key "your-key"

# Environment variable
export SKENE_API_KEY="your-key"

# Config file (interactive)
uvx skene config

Wrong provider for API key

Make sure the API key matches the provider. An OpenAI key won't work with --provider gemini.

Provider issues

Unknown provider

Valid provider names:

  • openai
  • gemini
  • anthropic or claude
  • lmstudio, lm-studio, or lm_studio
  • ollama
  • generic, openai-compatible, or openai_compatible

Generic provider: missing base URL

The generic provider requires a base URL:

uvx skene analyse-journey . --provider generic --base-url "http://localhost:8000/v1" --model "your-model"

Or set via environment variable:

export SKENE_BASE_URL="http://localhost:8000/v1"

File not found errors

Wrong bundle when running from another directory (push, journey)

If output_dir is not set in config, Skene picks ./skene-context vs ./skene by looking for those folders under the project path you pass to the command (for example skene push ./my-repo), not necessarily your shell's current directory.

If artifacts are still not found, set output_dir in .skene.config or SKENE_OUTPUT_DIR, or pass explicit paths (for example skene analyse-journey -o ./skene/journey.yaml on legacy-only trees).

See configuration: sticky output directory.

Rate limit errors

When a provider returns a rate limit error, skene silently falls back to a cheaper model. This keeps the workflow moving but means the output was generated by a different model than configured.

If you need output from a specific model (e.g. during benchmarking), use --no-fallback:

uvx skene analyse-journey . --no-fallback

With --no-fallback, the CLI retries the same model with exponential backoff. If all 3 retries are exhausted, the command raises an error instead of switching models.

Push / upstream issues

"No token" error

If push says "No token", you need to authenticate first:

uvx skene login --upstream https://skene.ai/workspace/my-app

Or set the token via environment variable:

export SKENE_UPSTREAM_API_KEY="your-token"

"No trigger migration found" or missing engine artifacts

push uploads existing artifacts: it does not generate them. Verify that:

  • skene-context/engine.yaml exists
  • supabase/migrations/*_skene_triggers.sql exists (or a legacy *skene_trigger* / *skene_telemetry* migration that push can detect)

Push authentication failed (401/403)

Your token may have expired or be invalid. Log out and log in again:

uvx skene logout
uvx skene login --upstream https://skene.ai/workspace/my-app

Debug mode

Use --debug on any command to show diagnostic messages on screen and log all LLM input and output to ~/.local/state/skene/debug/:

uvx skene analyse-journey . --debug
uvx skene push --debug

Debug mode can also be enabled via environment variable or config:

export SKENE_DEBUG=true
# .skene.config
debug = true

The debug logs show the full prompts sent to the LLM and the complete responses, which is useful for diagnosing unexpected output or provider-specific issues.

The general log file is located at ~/.local/state/skene/skene.log.

Getting help

  • GitHub issues: github.com/SkeneTechnologies/skene/issues
  • Documentation: www.skene.ai/resources/docs/skene
Previous← Python API
Skene

Product

How it worksFeaturesSupabaseArchitectureIntegrationsSecurityPricing

Resources

DocumentationGlossaryPlaybooksBlog

Company

AboutOpen sourceContactPrivacyTerms
© 2026 Skene. All rights reserved.
Privacy PolicyTerms of Service
Skene