Pangram verdict · v3.3
We believe that this document is fully human-written
AI likelihood · overall
HumanArticle text · 493 words · 2 segments analyzed
Bring your own AI Create flashcards from your terminal.
Create, search, and export decks straight from the shell. Pipe them into Claude, ChatGPT, or any LLM. Reviewing still happens in the Space app.
Install the Space app on Mac, Windows or Linux first. The CLI reads the database it keeps on your machine. No login, no API keys. Install Pick one New here? Install the Space app first and open it once, then pick one below. Homebrew macOS & Linuxbrew install space-org/tap/space-cliRecommended — updates automatically with `brew upgrade`. ★ Recommended for you curl installer macOS & Linuxcurl -fsSL https://raw.githubusercontent.com/space-org/space-cli/main/scripts/install.sh | shDrops the binary into ~/.local/bin. Works on any shell. ★ Recommended for you Manual download Windows, macOS, Linux Open latest release → Grab the archive for your platform and put the binary on your PATH. ★ Recommended for you Quickstart space deck list Show every deck with card and due counts space deck stats ck3u Retention, maturity mix, due today space card search "past tense" Full-text search across all cards space card show 7f2a Render a single card in the terminal space deck export ck3u --format csv Export a deck to CSV Run space --help for the full reference. deck, card and group each support create, show, list, edit, delete, search, stats and export. Pair it with AI.
Pipe structured data into any LLM. Get back analyses, explanations, new cards. A GUI cannot touch this.
Find confusing word pairs
Export a deck and let the AI scan every card at once. It spots false friends and overlapping meanings you miss one card at a time. $ space deck export ck3u --format json | claude \ "Which of these Spanish words have similar meanings I could easily confuse? Generate mnemonics for the most confusing pairs." Explain a tough card
When a card refuses to stick, ask for a deeper explanation. Linking new knowledge to old builds more retrieval paths.
$ space card show 7f2a | claude \ "Explain this concept with a hands-on example and an analogy to something I already know as a developer." Derive new cards from existing data
Answering before seeing the solution anchors knowledge deeper. Follow-up questions hit that mechanism. $ space deck export f02a --format json | claude \ "Analyze these system-design flashcards and create 10 follow-up questions. Format: JSON array with 'front' and 'back' per card." Any AI works. Claude, ChatGPT, Ollama, LM Studio: the CLI hands over the data, you pick the tool. With a local model, nothing leaves your machine. Sync across every device.
Cards you create in the CLI show up on your phone, tablet and desktop. Cards you learn on the go are queryable from the CLI right away.
Changes queue locally first. Next time the Space app is online, they sync to every device. No manual sync, no import or export, no cloud login in the CLI. Open source
Issues, contributions and a full command reference live on GitHub.
View on GitHub →