Repo-native continuity for AI engineering

ContextOS

Your AI engineering context follows the work, not the tool.

Checkpoint is the local-first CLI that helps developers resume work across AI coding tools without reconstructing the whole project from memory.

5-minute quickstart GitHub
Plan in Claude Code in Codex Debug in Claude Code Delegate to Antigravity Resume anywhere

Continuation pack

TaskImprove empty-project recovery
Inputslatest handoff, active task, constraints
NextClaude Code
Boundarylocal files you can inspect first
checkpoint continue 
$ checkpoint continue --from codex --for claude-code
Reading .contextos/handoffs/latest.md
Reading .contextos/tasks/active/TASK-004.md
Reading .contextos/context/constraints.md

# Continuation Pack
Current task: improve empty-project recovery
Next agent: claude-code
Status: source files ready to inspect

Resume with the thread intact.

Agents don't hand context to each other.

They read and write through ContextOS. Your context pack follows the work across every tool switch — no recap, no reconstruction.

Continuity layer
Claude → ContextOS → Codex → ContextOS → Claude Code → ContextOS → Antigravity → ContextOS → Claude

Not another coding agent. The continuity layer beneath them.

ContextOS keeps durable project memory where the repo can own it: readable files, explicit tasks, handoffs, decisions, and projections that existing tools already read.

1. Write

Local project memory

Keep constraints, decisions, active work, and handoffs in .contextos/ so the next session starts from something concrete.

2. Inspect

Files before prompts

Open the Markdown, read the generated pack, and choose what moves into the next AI tool.

3. Continue

Agent-shaped output

Ask for a pack aimed at Codex, Claude, Claude Code, Cursor, or a generic agent.

4. Resume

Less recap, more work

The next session gets the task, files to inspect, current status, and the next action without a long spoken reset.

A continuation pack is not a pitch deck.

It is a compact, readable handoff: what changed, what matters, where to look, and what the next agent should do first. 

# Continuation Pack

Current task: TASK-004 improve empty-project recovery
Previous agent: codex
Next agent: claude-code

## Files to inspect
- .contextos/tasks/active/TASK-004.md
- .contextos/handoffs/latest.md
- .contextos/context/constraints.md

## Next action
Reproduce the empty-project path and improve the recovery message.

Local trust before automation.

The first workflow is intentionally small: no account, no hidden database, no opaque project state. The repo gets readable context files, and you decide what to share with another tool. 

.contextos/
  context/
  tasks/
  handoffs/
  decisions/
  state/

Designed for inspection

The generated output uses obviously readable Markdown. The demo and examples use fake project names and safe placeholder values.

Try the shortest path first.

Install from PyPI, initialize project memory, and generate a continuation pack before wiring it into your real workflow. 

# pip
pip install checkpoint-cli

# uv
uv add checkpoint-cli

checkpoint setup-user
checkpoint init
checkpoint status
checkpoint continue
Start the 5-minute quickstart Read how it works