spaceshift

An interactive CLI research toolkit powered by LLMs. Branch into questions through tree structures, navigate the full space of perspectives, and grid-search evaluate across prompts and models to find what works best.

Full documentation at spcshft.com

# Launch interactive mode
spaceshift

# Select from guided menus:
# → Deep Research — decompose topics across all angles
# → Prompt Manipulate — explore prompt transformations
# → Compare Models — rank model responses
# → Grid Search — search across models × transforms
# → Prompt Tree — visualize exploration paths

All functionality is also available as a Python library for programmatic use.

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Install

pip install spaceshift

On first run, spaceshift will guide you through setting up your API keys:

$ spaceshift

No API keys found. Let's set up your providers.

  OpenAI (press Enter to skip): sk-proj-...
  ✓ OpenAI key saved

  Anthropic (press Enter to skip): sk-ant-...
  ✓ Anthropic key saved

  Google Gemini (press Enter to skip): [Enter]
  Together.AI (press Enter to skip): [Enter]
  xAI (press Enter to skip): [Enter]

✓ Configuration saved to ~/.spaceshift/config.json

Keys are stored securely in ~/.spaceshift/config.json and available globally. You can update or add keys anytime via the "Manage API Keys" option in the main menu.

For Python library usage: You can still use a .env file in your project directory - it will be loaded automatically when you import spaceshift.

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Interactive CLI

Launch the interactive mode:

spaceshift

The CLI guides you through:

• Deep Research — Decompose a topic and explore all angles (sub/super/side directions)
• Prompt Manipulate — Transform prompts and explore variations
• Compare Models — Run the same prompt across models and rank responses
• Grid Search — Search across models × transforms simultaneously
• Prompt Tree — Visualize the exploration space
• Manage API Keys — Add, update, or view your configured API providers

Select your research mode, pick a model from categorized rankings (optimal, best, fast, cheap, open), enter your prompt, and let spaceshift generate comprehensive research outputs. Results are saved as structured markdown with YAML frontmatter, and the built-in viewer opens automatically.

After research completes, an autonomous agent post-processes all outputs to generate synthesis documents that help you understand the overall findings. The agent reads all markdown files, analyzes the tree structure, and decides what synthesis documents would be most valuable — updating you on progress along the way.

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Viewing Results

Browse any output directory in the browser with the built-in viewer:

spaceshift view output_directory

Two-panel layout: sidebar with smart-sorted file list, content area with rendered markdown and frontmatter metadata cards. No dependencies — runs on Python's stdlib server with client-side markdown rendering.

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Advanced Usage

While spaceshift is designed as a CLI tool, advanced users can import and use the underlying modules programmatically. This is unsupported — the CLI is the primary interface, and internal APIs may change without notice.

For those who want to explore anyway, the main modules are in spaceshift/ including LLM, research_tree, compare_models, grid_search, etc. See the source code for details.