compact

Compact session messages by writing HANDOFF.md and injecting summaries into CLAUDE.md.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/edri2or/ripo-skills-main --skill compact-edri2or
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: compact
Source: https://github.com/edri2or/ripo-skills-main/tree/main/exported-skills/compact
Command: npx skills add https://github.com/edri2or/ripo-skills-main --skill compact-edri2or

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Compact conversation context to reduce token load while preserving essential meaning during AI sessions.

Core Features & Use Cases

  • Writes HANDOFF.md reflecting session diffs to preserve history.
  • Injects a summary into CLAUDE.md under the Session Handoff section to maintain continuity.
  • Signals compact-ready to allow safe token compression without losing critical context.

Quick Start

Invoke the /compact sequence to create HANDOFF.md, inject a Session Handoff into CLAUDE.md, and emit a compact-ready signal.

Frequently Asked Questions about compact

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

FAQPage Schema
How do I compress long conversation context to reduce token load in AI-agent sessions?

To compress long conversation context, you can compact session messages by writing session diffs to HANDOFF.md and injecting a summary into CLAUDE.md, which preserves essential content while reducing token load.

What is the best way to preserve AI session history before hitting token limits?

The best way to preserve AI session history before hitting token limits is to write a HANDOFF.md file reflecting session diffs, ensuring continuity and critical context are maintained during extended dialogues.

How does writing a HANDOFF.md file improve memory management for extended AI dialogues?

Writing a HANDOFF.md file improves memory management by capturing session diffs externally, allowing the AI-agent to safely compact token-heavy messages without losing essential historical context.

Can I maintain conversation continuity after compacting session messages?

Yes, you can maintain conversation continuity by injecting a summary into the Session Handoff section of CLAUDE.md, which allows the AI-agent to recall essential context after message compaction.

When should I trigger a compact-ready signal during an AI-agent session?

You should trigger a compact-ready signal when token limits are approaching and you have safely written HANDOFF.md and injected the session summary into CLAUDE.md to prevent losing critical context.

Does compacting an AI session context require any external dependencies?

No, compacting an AI session context does not require external dependencies, as the workflow operates by detecting and writing to local HANDOFF.md and CLAUDE.md files to manage token limits internally.