signal-ckpt

Compress session state into a ≤50-token CKPT checkpoint.

10|Updated Apr 15, 2026
One-click install
npx skills add https://github.com/mattbaconz/signal --skill signal-ckpt
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: signal-ckpt
Source: https://github.com/mattbaconz/signal/tree/main/gemini-signal/skills/signal-ckpt
Command: npx skills add https://github.com/mattbaconz/signal --skill signal-ckpt

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Compresses the current session state into a compact checkpoint to drop prior history and save tokens.

Core Features & Use Cases

  • Manual checkpoint via /signal-ckpt, "checkpoint", or "save state".
  • Automatic checkpoint in SIGNAL-3 mode every 5 turns.
  • Outputs a CKPT[N] block with a minimal, deterministic format that collapses conversation history to a ≤50-token state atom.

Quick Start

Invoke the checkpoint by saying /signal-ckpt or using the word 'checkpoint' to generate a compact session state you can resume from.

Frequently Asked Questions about signal-ckpt

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

FAQPage Schema
How do I compress conversation history to save tokens in a long-running AI session?

You can compress conversation history by triggering a checkpoint with /signal-ckpt or the word "checkpoint". This collapses prior context into a ≤50-token state atom, dropping old history while preserving the next actionable item to free up token limits.

What is a session checkpoint and when do I need to create one?

A session checkpoint is a compact, deterministic state block that captures essential conversation context. You need to create one during long-running, context-heavy tasks to prevent hitting token limits and preserve critical state for resumption.

Can I automatically save session state every few turns during context-heavy tasks?

Yes, you can automatically save session state every five turns by enabling SIGNAL-3 mode. This auto-triggers the checkpoint mechanism to compress ongoing context-heavy conversations into a durable state block without manual intervention.

Does the checkpoint format preserve the next actionable item when dropping prior history?

Yes, the checkpoint format preserves the next actionable item when dropping prior history. It uses a deterministic CKPT format and collapse algorithm to ensure the compressed state stays within the 50-token limit while retaining essential task continuity.

What is the best way to manage token limits in long-running conversations without losing context?

The best way to manage token limits in long-running conversations is to generate a concise checkpoint. Compressing the session state into a ≤50-token block drops bulky prior history while retaining the essential state needed to resume the task.