About this project
Awesome AI Cheatsheets is a curated collection of standardized references for terminal-native AI coding agents and the concepts behind them. Our wedge: format + freshness + comparability — every cheatsheet ships with a last-updated date, is flagged when it goes stale, and follows the same 7-section structure so you can compare tools head-to-head.
The wedge
We sit between shallow READMEs that skip the nuance and exhaustive reference docs that bury the lede. Three properties make a cheatsheet worth landing on:
- Format. Every entry follows the same locked 7-section template — one-liner, mental model, quickstart, recipes, gotchas, reference, links — so you can skim it the same way every time.
- Freshness. Each cheatsheet carries a
last_updateddate and astale_after_daysbudget. When a cheatsheet drifts past its budget, the catalog and detail pages flag it as may be stale in plain sight. - Comparability. Because the structure is fixed, mutually-relevant entries (e.g. two CLI agents) can be diffed section-by-section without re-learning each one's layout.
How it works
- The catalog lists every published cheatsheet with its category, tags, and last-updated date.
- A built-in search (Pagefind) indexes every entry at build time — no third-party JavaScript, no runtime API.
- Filter pills let you narrow by category (tool, mcp, concept, comparison) or by tag.
- A freshness chip on each detail page surfaces the last-updated date and a stale banner when the entry is past its budget.
Contribute
Cheatsheets are authored with Claude Code and the
/cheatsheet-scribe skill. The
30-minute contributor tutorial walks
through the full flow — from raw notes to a merged PR.
- Contributor tutorial (docs/contributing.md)
- Project requirements document (PRD.md)
- Source repository on GitHub