alive:save

Automates checkpointing of stash and session state across bundles.

124|7|Updated Feb 19, 2026
One-click install
npx skills add https://github.com/alivecontext/alive --skill alive-save
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: alive:save
Source: https://github.com/alivecontext/alive/tree/main/plugins/alive/skills/save
Command: npx skills add https://github.com/alivecontext/alive --skill alive-save

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Checkpointing is essential to prevent loss of progress in long AI sessions. This skill automates saving the current stash, updating runtime state, and preserving a recoverable trail for future sessions.

Core Features & Use Cases

  • Full save protocol: confirms stash, writes a log, updates state, generates projections, dispatches, and resets.
  • Non-terminating checkpoint: saves can occur multiple times; each save increments the saves: counter and updates last_saved:.
  • Edge-case resilience: handles missing context gracefully and ensures post-save consistency across bundles.

Quick Start

Invoke the save flow to checkpoint the stash, update state, and generate projections.

Frequently Asked Questions about alive:save

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate session state checkpointing in long-running AI workflows?

Automating session state checkpointing saves the current stash, updates runtime state, and generates recoverable projections to prevent data loss during long-running AI sessions. Each save increments a counter and logs the update for future recovery.

When do I need to checkpoint and save my session state?

You need to checkpoint and save your session state during long-running AI sessions that span multiple bundles. Checkpointing preserves a recoverable trail of logs and state updates if the session is interrupted or needs to be resumed later.

How do I save and reset my workflow stash across multiple bundles?

Saving and resetting your workflow stash requires invoking a full save protocol that confirms the stash, writes a log, updates state, generates projections, and dispatches. This coordinates save actions across the active bundle to ensure post-save consistency.

Does automated checkpointing handle missing context in active bundles?

Automated checkpointing handles missing context gracefully and ensures post-save consistency across bundles. This edge-case resilience allows the save flow to continue executing projections and state updates without failing the entire session.

What do I need to coordinate checkpoint saves and projections?

To coordinate checkpoint saves and projections, you need access to kernel logs, context manifests, and the active bundle. These inputs allow the save flow to accurately update runtime state and preserve the session stash.